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Posted to commits@hivemall.apache.org by my...@apache.org on 2018/12/26 10:22:49 UTC
[01/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Repository: incubator-hivemall-site
Updated Branches:
refs/heads/asf-site 82c62b0e0 -> d9012d92a
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/troubleshooting/oom.html
----------------------------------------------------------------------
diff --git a/userguide/troubleshooting/oom.html b/userguide/troubleshooting/oom.html
index 7f90a7a..4f68830 100644
--- a/userguide/troubleshooting/oom.html
+++ b/userguide/troubleshooting/oom.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2382,7 +2427,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2412,7 +2457,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[20/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/ft_engineering/quantify.html
----------------------------------------------------------------------
diff --git a/userguide/ft_engineering/quantify.html b/userguide/ft_engineering/quantify.html
index 5213478..4ff9cc0 100644
--- a/userguide/ft_engineering/quantify.html
+++ b/userguide/ft_engineering/quantify.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2520,7 +2565,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
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<b>6.2.1.</b>
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<b>6.2.2.</b>
+ General Binary Classifier
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+
+
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+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
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Logistic Regression
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- Mini-batch gradient descent
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</a>
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<b>6.3.1.</b>
- Data preparation
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
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+
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
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</a>
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<b>8.2.1.</b>
- Data preparation
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</a>
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- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
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+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
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+ Top-k Join Processing
</a>
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+ Other Utility Functions
</a>
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+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
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Logistic Regression
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</a>
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<b>6.3.4.</b>
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Random Forest
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<b>6.6.1.</b>
- Data pareparation
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</a>
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- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Data preparation for one-vs-the-rest classifiers
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</a>
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- one-vs-the-rest classifier
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</a>
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<b>9.2.1.</b>
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</a>
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<b>9.3.1.</b>
- Data preparation
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Logistic Regression
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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- Data preparation
+ Data Preparation
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2513,7 +2558,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2543,7 +2588,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[18/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/getting_started/permanent-functions.html
----------------------------------------------------------------------
diff --git a/userguide/getting_started/permanent-functions.html b/userguide/getting_started/permanent-functions.html
index 5992fda..5ad766d 100644
--- a/userguide/getting_started/permanent-functions.html
+++ b/userguide/getting_started/permanent-functions.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2405,7 +2450,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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Random Forest
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</a>
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<b>7.1.1.</b>
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Random Forest
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</a>
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</a>
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+ gitbook.page.hasChanged({"page":{"title":"List of Functions","level":"1.3","depth":1,"next":{"title":"Tips for Effective Hivemall","level":"1.4","depth":1,"path":"tips/README.md","ref":"tips/README.md","articles":[{"title":"Explicit add_bias() for better prediction","level":"1.4.1","depth":2,"path":"tips/addbias.md","ref":"tips/addbias.md","articles":[]},{"title":"Use rand_amplify() to better prediction results","level":"1.4.2","depth":2,"path":"tips/rand_amplify.md","ref":"tips/rand_amplify.md","articles":[]},{"title":"Real-time prediction on RDBMS","level":"1.4.3","depth":2,"path":"tips/rt_prediction.md","ref":"tips/rt_prediction.md","articles":[]},{"title":"Ensemble learning for stable prediction","level":"1.4.4","depth":2,"path":"tips/ensemble_learning.md","ref":"tips/ensemble_learning.md","articles":[]},{"title":"Mixing models for a better prediction convergence (MIX server)","level":"1.4.5","depth":2,"path":"tips/mixserver.md","ref":"tips/mixserver.md","articles":[
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</script>
</div>
@@ -2931,7 +2976,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[11/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/regression/e2006_arow.html
----------------------------------------------------------------------
diff --git a/userguide/regression/e2006_arow.html b/userguide/regression/e2006_arow.html
index c95408e..473cbce 100644
--- a/userguide/regression/e2006_arow.html
+++ b/userguide/regression/e2006_arow.html
@@ -100,7 +100,7 @@
<link rel="next" href="kddcup12tr2.html" />
- <link rel="prev" href="e2006_dataset.html" />
+ <link rel="prev" href="e2006_generic.html" />
</head>
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter active" data-level="8.2.2" data-path="e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="e2006_generic.html">
- <a href="e2006_arow.html">
+ <a href="e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter active" data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2317,11 +2362,40 @@
specific language governing permissions and limitations
under the License.
-->
-<p><a href="https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/regression.html#E2006-tfidf" target="_blank">https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/regression.html#E2006-tfidf</a></p>
-<hr>
-<h1 id="pa1a">[PA1a]</h1>
+<!-- toc --><div id="toc" class="toc">
+
+<ul>
+<li><a href="#pa1a">PA1a</a><ul>
+<li><a href="#training">Training</a></li>
+<li><a href="#prediction">prediction</a></li>
+<li><a href="#evaluation">evaluation</a></li>
+</ul>
+</li>
+<li><a href="#pa2a">PA2a</a><ul>
+<li><a href="#training-1">Training</a></li>
+<li><a href="#prediction-1">prediction</a></li>
+<li><a href="#evaluation-1">evaluation</a></li>
+</ul>
+</li>
+<li><a href="#arow">AROW</a><ul>
+<li><a href="#training-2">Training</a></li>
+<li><a href="#prediction-2">prediction</a></li>
+<li><a href="#evaluation-2">evaluation</a></li>
+</ul>
+</li>
+<li><a href="#arowe">AROWe</a><ul>
+<li><a href="#training-3">Training</a></li>
+<li><a href="#prediction-3">prediction</a></li>
+<li><a href="#evaluation-3">evaluation</a></li>
+</ul>
+</li>
+</ul>
+
+</div><!-- tocstop -->
+<h1 id="pa1a">PA1a</h1>
<h2 id="training">Training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">64</span>;
+
<span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_pa1a_model ;
<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> e2006tfidf_pa1a_model <span class="hljs-keyword">as</span>
<span class="hljs-keyword">select</span>
@@ -2334,9 +2408,11 @@
e2006tfidf_train_x3
) t
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature;
+
+<span class="hljs-comment">-- reset to the default setting</span>
<span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">-1</span>;
</code></pre>
-<p><em>Caution: Do not use voted_avg() for regression. voted_avg() is for classification.</em></p>
+<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p>Do not use <code>voted_avg()</code> for regression. <code>voted_avg()</code> is for classification.</p></div></div>
<h2 id="prediction">prediction</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> e2006tfidf_pa1a_predict
<span class="hljs-keyword">as</span>
@@ -2350,35 +2426,42 @@
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_pa1a_submit;
-<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> e2006tfidf_pa1a_submit <span class="hljs-keyword">as</span>
-<span class="hljs-keyword">select</span>
- t.target <span class="hljs-keyword">as</span> actual,
- p.predicted <span class="hljs-keyword">as</span> predicted
-<span class="hljs-keyword">from</span>
- e2006tfidf_test t <span class="hljs-keyword">JOIN</span> e2006tfidf_pa1a_predict p
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>);
-
-<span class="hljs-keyword">select</span> <span class="hljs-keyword">avg</span>(actual), <span class="hljs-keyword">avg</span>(predicted) <span class="hljs-keyword">from</span> e2006tfidf_pa1a_submit;
-</code></pre>
-<blockquote>
-<p>-3.8200363760415414 -3.8869923258589476</p>
-</blockquote>
-<pre><code class="lang-sql"><span class="hljs-keyword">set</span> hivevar:mean_actual=<span class="hljs-number">-3.8200363760415414</span>;
-
+<pre><code class="lang-sql">WITH submit as (
+ <span class="hljs-keyword">select</span>
+ t.target <span class="hljs-keyword">as</span> actual,
+ p.predicted <span class="hljs-keyword">as</span> predicted
+ <span class="hljs-keyword">from</span>
+ e2006tfidf_test t
+ <span class="hljs-keyword">JOIN</span> e2006tfidf_pa1a_predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
<span class="hljs-keyword">select</span>
- <span class="hljs-keyword">sqrt</span>(<span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)) <span class="hljs-keyword">as</span> RMSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">abs</span>(predicted - actual))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MAE,
- <span class="hljs-number">1</span> - <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - predicted,<span class="hljs-number">2.0</span>)) / <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - ${mean_actual},<span class="hljs-number">2.0</span>)) <span class="hljs-keyword">as</span> R2
+ rmse(predicted, actual) <span class="hljs-keyword">as</span> RMSE,
+ mse(predicted, actual) <span class="hljs-keyword">as</span> MSE,
+ mae(predicted, actual) <span class="hljs-keyword">as</span> MAE,
+ r2(predicted, actual) <span class="hljs-keyword">as</span> R2
<span class="hljs-keyword">from</span>
- e2006tfidf_pa1a_submit;
+ submit;
</code></pre>
-<blockquote>
-<p>0.3797959864675519 0.14424499133686086 0.23846059576113587 0.5010367946980386</p>
-</blockquote>
-<hr>
-<h1 id="pa2a">[PA2a]</h1>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">rmse</th>
+<th style="text-align:center">mse</th>
+<th style="text-align:center">mae</th>
+<th style="text-align:center">r2</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">0.3797959864675519</td>
+<td style="text-align:center">0.14424499133686086</td>
+<td style="text-align:center">0.23846059576113587</td>
+<td style="text-align:center">0.5010367946980386</td>
+</tr>
+</tbody>
+</table>
+<h1 id="pa2a">PA2a</h1>
<h2 id="training">Training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">64</span>;
<span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_pa2a_model;
@@ -2408,35 +2491,42 @@
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_pa2a_submit;
-<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> e2006tfidf_pa2a_submit <span class="hljs-keyword">as</span>
-<span class="hljs-keyword">select</span>
- t.target <span class="hljs-keyword">as</span> actual,
- pd.predicted <span class="hljs-keyword">as</span> predicted
-<span class="hljs-keyword">from</span>
- e2006tfidf_test t <span class="hljs-keyword">JOIN</span> e2006tfidf_pa2a_predict pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
-
-<span class="hljs-keyword">select</span> <span class="hljs-keyword">avg</span>(actual), <span class="hljs-keyword">avg</span>(predicted) <span class="hljs-keyword">from</span> e2006tfidf_pa2a_submit;
-</code></pre>
-<blockquote>
-<p>-3.8200363760415414 -3.9124877451612488</p>
-</blockquote>
-<pre><code class="lang-sql"><span class="hljs-keyword">set</span> hivevar:mean_actual=<span class="hljs-number">-3.8200363760415414</span>;
-
+<pre><code class="lang-sql">WITH submit as (
+ <span class="hljs-keyword">select</span>
+ t.target <span class="hljs-keyword">as</span> actual,
+ p.predicted <span class="hljs-keyword">as</span> predicted
+ <span class="hljs-keyword">from</span>
+ e2006tfidf_test t
+ <span class="hljs-keyword">JOIN</span> e2006tfidf_pa2a_predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
<span class="hljs-keyword">select</span>
- <span class="hljs-keyword">sqrt</span>(<span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)) <span class="hljs-keyword">as</span> RMSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">abs</span>(predicted - actual))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MAE,
- <span class="hljs-number">1</span> - <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - predicted,<span class="hljs-number">2.0</span>)) / <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - ${mean_actual},<span class="hljs-number">2.0</span>)) <span class="hljs-keyword">as</span> R2
+ rmse(predicted, actual) <span class="hljs-keyword">as</span> RMSE,
+ mse(predicted, actual) <span class="hljs-keyword">as</span> MSE,
+ mae(predicted, actual) <span class="hljs-keyword">as</span> MAE,
+ r2(predicted, actual) <span class="hljs-keyword">as</span> R2
<span class="hljs-keyword">from</span>
- e2006tfidf_pa2a_submit;
+ submit;
</code></pre>
-<blockquote>
-<p>0.38538660838804495 0.14852283792484033 0.2466732002711477 0.48623913673053565</p>
-</blockquote>
-<hr>
-<h1 id="arow">[AROW]</h1>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">rmse</th>
+<th style="text-align:center">mse</th>
+<th style="text-align:center">mae</th>
+<th style="text-align:center">r2</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">0.38538660838804495</td>
+<td style="text-align:center">0.14852283792484033</td>
+<td style="text-align:center">0.2466732002711477</td>
+<td style="text-align:center">0.48623913673053565</td>
+</tr>
+</tbody>
+</table>
+<h1 id="arow">AROW</h1>
<h2 id="training">Training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">64</span>;
<span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_arow_model ;
@@ -2468,35 +2558,42 @@
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_arow_submit;
-<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> e2006tfidf_arow_submit <span class="hljs-keyword">as</span>
-<span class="hljs-keyword">select</span>
- t.target <span class="hljs-keyword">as</span> actual,
- p.predicted <span class="hljs-keyword">as</span> predicted
-<span class="hljs-keyword">from</span>
- e2006tfidf_test t <span class="hljs-keyword">JOIN</span> e2006tfidf_arow_predict p
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>);
-
-<span class="hljs-keyword">select</span> <span class="hljs-keyword">avg</span>(actual), <span class="hljs-keyword">avg</span>(predicted) <span class="hljs-keyword">from</span> e2006tfidf_arow_submit;
-</code></pre>
-<blockquote>
-<p>-3.8200363760415414 -3.8692518911517433</p>
-</blockquote>
-<pre><code class="lang-sql"><span class="hljs-keyword">set</span> hivevar:mean_actual=<span class="hljs-number">-3.8200363760415414</span>;
-
+<pre><code class="lang-sql">WITH submit as (
+ <span class="hljs-keyword">select</span>
+ t.target <span class="hljs-keyword">as</span> actual,
+ p.predicted <span class="hljs-keyword">as</span> predicted
+ <span class="hljs-keyword">from</span>
+ e2006tfidf_test t
+ <span class="hljs-keyword">JOIN</span> e2006tfidf_arow_predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
<span class="hljs-keyword">select</span>
- <span class="hljs-keyword">sqrt</span>(<span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)) <span class="hljs-keyword">as</span> RMSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">abs</span>(predicted - actual))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MAE,
- <span class="hljs-number">1</span> - <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - predicted,<span class="hljs-number">2.0</span>)) / <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - ${mean_actual},<span class="hljs-number">2.0</span>)) <span class="hljs-keyword">as</span> R2
+ rmse(predicted, actual) <span class="hljs-keyword">as</span> RMSE,
+ mse(predicted, actual) <span class="hljs-keyword">as</span> MSE,
+ mae(predicted, actual) <span class="hljs-keyword">as</span> MAE,
+ r2(predicted, actual) <span class="hljs-keyword">as</span> R2
<span class="hljs-keyword">from</span>
- e2006tfidf_arow_submit;
+ submit;
</code></pre>
-<blockquote>
-<p>0.37862513029019407 0.14335698928726642 0.2368787001269389 0.5041085155590119</p>
-</blockquote>
-<hr>
-<h1 id="arowe">[AROWe]</h1>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">rmse</th>
+<th style="text-align:center">mse</th>
+<th style="text-align:center">mae</th>
+<th style="text-align:center">r2</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">0.37862513029019407</td>
+<td style="text-align:center">0.14335698928726642</td>
+<td style="text-align:center">0.2368787001269389</td>
+<td style="text-align:center">0.5041085155590119</td>
+</tr>
+</tbody>
+</table>
+<h1 id="arowe">AROWe</h1>
<p>AROWe is a modified version of AROW that uses Hinge loss (epsilion = 0.1)</p>
<h2 id="training">Training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">64</span>;
@@ -2529,33 +2626,41 @@
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_arowe_submit;
-<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> e2006tfidf_arowe_submit <span class="hljs-keyword">as</span>
-<span class="hljs-keyword">select</span>
- t.target <span class="hljs-keyword">as</span> actual,
- p.predicted <span class="hljs-keyword">as</span> predicted
-<span class="hljs-keyword">from</span>
- e2006tfidf_test t <span class="hljs-keyword">JOIN</span> e2006tfidf_arowe_predict p
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>);
-
-<span class="hljs-keyword">select</span> <span class="hljs-keyword">avg</span>(actual), <span class="hljs-keyword">avg</span>(predicted) <span class="hljs-keyword">from</span> e2006tfidf_arowe_submit;
-</code></pre>
-<blockquote>
-<p>-3.8200363760415414 -3.86494905688414</p>
-</blockquote>
-<pre><code class="lang-sql"><span class="hljs-keyword">set</span> hivevar:mean_actual=<span class="hljs-number">-3.8200363760415414</span>;
-
+<pre><code class="lang-sql">WITH submit as (
+ <span class="hljs-keyword">select</span>
+ t.target <span class="hljs-keyword">as</span> actual,
+ p.predicted <span class="hljs-keyword">as</span> predicted
+ <span class="hljs-keyword">from</span>
+ e2006tfidf_test t
+ <span class="hljs-keyword">JOIN</span> e2006tfidf_arowe_predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
<span class="hljs-keyword">select</span>
- <span class="hljs-keyword">sqrt</span>(<span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)) <span class="hljs-keyword">as</span> RMSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(predicted - actual,<span class="hljs-number">2.0</span>))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MSE,
- <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">abs</span>(predicted - actual))/<span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> MAE,
- <span class="hljs-number">1</span> - <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - predicted,<span class="hljs-number">2.0</span>)) / <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">pow</span>(actual - ${mean_actual},<span class="hljs-number">2.0</span>)) <span class="hljs-keyword">as</span> R2
+ rmse(predicted, actual) <span class="hljs-keyword">as</span> RMSE,
+ mse(predicted, actual) <span class="hljs-keyword">as</span> MSE,
+ mae(predicted, actual) <span class="hljs-keyword">as</span> MAE,
+ r2(predicted, actual) <span class="hljs-keyword">as</span> R2
<span class="hljs-keyword">from</span>
- e2006tfidf_arowe_submit;
+ submit;
</code></pre>
-<blockquote>
-<p>0.37789148212861856 0.14280197226536404 0.2357339155291536 0.5060283955470721</p>
-</blockquote>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">rmse</th>
+<th style="text-align:center">mse</th>
+<th style="text-align:center">mae</th>
+<th style="text-align:center">r2</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">0.37789148212861856</td>
+<td style="text-align:center">0.14280197226536404</td>
+<td style="text-align:center">0.2357339155291536</td>
+<td style="text-align:center">0.5060283955470721</td>
+</tr>
+</tbody>
+</table>
<p><div id="page-footer" class="localized-footer"><hr><!--
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
@@ -2611,7 +2716,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"Passive Aggressive, AROW","level":"8.2.2","depth":2,"next":{"title":"KDDCup 2012 Track 2 CTR Prediction Tutorial","level":"8.3","depth":1,"path":"regression/kddcup12tr2.md","ref":"regression/kddcup12tr2.md","articles":[{"title":"Data preparation","level":"8.3.1","depth":2,"path":"regression/kddcup12tr2_dataset.md","ref":"regression/kddcup12tr2_dataset.md","articles":[]},{"title":"Logistic Regression, Passive Aggressive","level":"8.3.2","depth":2,"path":"regression/kddcup12tr2_lr.md","ref":"regression/kddcup12tr2_lr.md","articles":[]},{"title":"Logistic Regression with amplifier","level":"8.3.3","depth":2,"path":"regression/kddcup12tr2_lr_amplify.md","ref":"regression/kddcup12tr2_lr_amplify.md","articles":[]},{"title":"AdaGrad, AdaDelta","level":"8.3.4","depth":2,"path":"regression/kddcup12tr2_adagrad.md","ref":"regression/kddcup12tr2_adagrad.md","articles":[]}]},"previous":{"title":"Data preparation","level":"8.2.1","depth":2,"pa
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});
</script>
</div>
@@ -2641,7 +2746,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/regression/e2006_dataset.html
----------------------------------------------------------------------
diff --git a/userguide/regression/e2006_dataset.html b/userguide/regression/e2006_dataset.html
index 7305822..6215927 100644
--- a/userguide/regression/e2006_dataset.html
+++ b/userguide/regression/e2006_dataset.html
@@ -4,7 +4,7 @@
<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>Data preparation · Hivemall User Manual</title>
+ <title>Data Preparation · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
@@ -97,7 +97,7 @@
<link rel="shortcut icon" href="../gitbook/images/favicon.ico" type="image/x-icon">
- <link rel="next" href="e2006_arow.html" />
+ <link rel="next" href="e2006_generic.html" />
<link rel="prev" href="e2006.html" />
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
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Random Forest
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+ Data Preparation
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+ Data Preparation
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+ Item-based Collaborative Filtering
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<b>13.2.1.</b>
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<b>13.4.</b>
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[06/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/spark/getting_started/installation.html
----------------------------------------------------------------------
diff --git a/userguide/spark/getting_started/installation.html b/userguide/spark/getting_started/installation.html
index 293040d..41bee59 100644
--- a/userguide/spark/getting_started/installation.html
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<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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<b>6.2.2.</b>
+ General Binary Classifier
+
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+
+
+
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+
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+
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Logistic Regression
</a>
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<a href="../../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
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+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.3.4.</b>
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+
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+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
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Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
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+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ LSH/MinHash and Jaccard Similarity
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+ LSH/MinHash and Brute-force Search
</a>
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- Data preparation
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+ Item-based Collaborative Filtering
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+ a9a Tutorial for DataFrame
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+ E2006-tfidf Regression Tutorial for SQL
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+ Generic Features
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+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
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+ Other Utility Functions
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+ Item-based Collaborative Filtering
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- E2006-tfidf regression tutorial for SQL
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- Generic features
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<h1>
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<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
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<b>6.2.2.</b>
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+
+
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Logistic Regression
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.5.1.</b>
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+ Data Preparation
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<b>8.2.2.</b>
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+
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
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+ SLIM for fast top-k Recommendation
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+ 10-fold Cross Validation (Matrix Factorization)
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+ a9a Tutorial for DataFrame
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+ a9a Tutorial for SQL
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
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- Top-k join processing
+ Top-k Join Processing
</a>
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[12/33] incubator-hivemall-site git commit: Update tutorial for
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<b>6.2.1.</b>
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<b>6.2.2.</b>
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Logistic Regression
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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- Top-k join processing
+ Top-k Join Processing
</a>
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<b>13.4.2.</b>
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index a326179..787dc02 100644
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<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>LSH/MinHash and Jaccard similarity · Hivemall User Manual</title>
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<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
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<b>6.2.1.</b>
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+ Data Preparation
</a>
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</li>
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+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >LSH/MinHash and Jaccard similarity</a>
+ <a href=".." >LSH/MinHash and Jaccard Similarity</a>
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<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
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<b>6.2.2.</b>
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Logistic Regression
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
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<b>6.6.1.</b>
- Data pareparation
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<b>6.8.1.</b>
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</a>
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<b>7.1.1.</b>
- Data preparation
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</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
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</a>
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<b>7.1.6.</b>
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<b>8.2.1.</b>
- Data preparation
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<b>8.2.2.</b>
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+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
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<b>13.2.1.</b>
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+ a9a Tutorial for DataFrame
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+ E2006-tfidf Regression Tutorial for DataFrame
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- E2006-tfidf regression tutorial for SQL
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+ Top-k Join Processing
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<b>13.4.2.</b>
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</a>
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<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
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<b>6.2.2.</b>
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Logistic Regression
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<b>6.3.1.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
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</a>
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<b>6.6.1.</b>
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</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="e2006_generic.html">
- <a href="e2006_arow.html">
+ <a href="e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
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@@ -2402,7 +2447,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[19/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/ft_engineering/vectorization.html
----------------------------------------------------------------------
diff --git a/userguide/ft_engineering/vectorization.html b/userguide/ft_engineering/vectorization.html
index ed0a555..3269a12 100644
--- a/userguide/ft_engineering/vectorization.html
+++ b/userguide/ft_engineering/vectorization.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2410,7 +2455,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2440,7 +2485,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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index 2c0bfb0..2d87f04 100644
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<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
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Logistic Regression
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</a>
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<b>6.3.1.</b>
- Data preparation
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
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+ </a>
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+
+
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+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
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+
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
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</a>
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<b>6.8.1.</b>
- Data preparation
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</a>
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<b>7.1.1.</b>
- Data preparation
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</a>
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<b>7.1.2.</b>
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</a>
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<b>8.2.2.</b>
+ General Regessor
+
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+
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+
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Passive Aggressive, AROW
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<b>8.3.1.</b>
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</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
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</a>
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</a>
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<b>13.2.1.</b>
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- E2006-tfidf regression tutorial for SQL
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</a>
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<b>13.4.</b>
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</a>
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----------------------------------------------------------------------
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<b>6.2.2.</b>
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+
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Logistic Regression
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- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
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</a>
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</li>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
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</a>
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<b>8.2.1.</b>
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</a>
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<b>8.2.2.</b>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ LSH/MinHash and Jaccard Similarity
</a>
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+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
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</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
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</a>
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</a>
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</a>
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Random Forest
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</a>
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<b>7.1.1.</b>
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<b>6.2.2.</b>
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Random Forest
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</a>
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<b>7.1.1.</b>
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</a>
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<b>13.4.</b>
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+ Generic Features
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@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
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+ Other Utility Functions
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[33/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
Update tutorial for general classifier/regressor
Project: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/commit/d9012d92
Tree: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/tree/d9012d92
Diff: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/diff/d9012d92
Branch: refs/heads/asf-site
Commit: d9012d92a95fab42acb8cc7580af6a58d32fb7c3
Parents: 82c62b0
Author: Makoto Yui <my...@apache.org>
Authored: Wed Dec 26 19:22:26 2018 +0900
Committer: Makoto Yui <my...@apache.org>
Committed: Wed Dec 26 19:22:26 2018 +0900
----------------------------------------------------------------------
userguide/anomaly/changefinder.html | 123 +-
userguide/anomaly/lof.html | 123 +-
userguide/anomaly/sst.html | 123 +-
userguide/binaryclass/a9a.html | 123 +-
userguide/binaryclass/a9a_dataset.html | 129 +-
userguide/binaryclass/a9a_generic.html | 2620 ++++++++++++++++++
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userguide/binaryclass/a9a_minibatch.html | 139 +-
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userguide/binaryclass/kdd2010b.html | 123 +-
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userguide/binaryclass/news20_adagrad.html | 160 +-
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.../news20_one-vs-the-rest_dataset.html | 127 +-
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userguide/recommend/news20_jaccard.html | 127 +-
userguide/recommend/news20_knn.html | 127 +-
userguide/regression/e2006.html | 123 +-
userguide/regression/e2006_arow.html | 397 ++-
userguide/regression/e2006_dataset.html | 129 +-
userguide/regression/e2006_generic.html | 2574 +++++++++++++++++
userguide/regression/general.html | 123 +-
userguide/regression/kddcup12tr2.html | 123 +-
userguide/regression/kddcup12tr2_adagrad.html | 123 +-
userguide/regression/kddcup12tr2_dataset.html | 127 +-
userguide/regression/kddcup12tr2_lr.html | 123 +-
.../regression/kddcup12tr2_lr_amplify.html | 123 +-
userguide/search_index.json | 2 +-
userguide/sitemap.xml | 3 +
userguide/spark/binaryclass/a9a_df.html | 127 +-
userguide/spark/binaryclass/a9a_sql.html | 127 +-
userguide/spark/binaryclass/index.html | 123 +-
userguide/spark/getting_started/index.html | 123 +-
.../spark/getting_started/installation.html | 123 +-
userguide/spark/misc/functions.html | 127 +-
userguide/spark/misc/misc.html | 127 +-
userguide/spark/misc/topk_join.html | 127 +-
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userguide/supervised_learning/prediction.html | 248 +-
userguide/supervised_learning/tutorial.html | 166 +-
userguide/tips/addbias.html | 123 +-
userguide/tips/emr.html | 123 +-
userguide/tips/ensemble_learning.html | 123 +-
userguide/tips/general_tips.html | 123 +-
userguide/tips/hadoop_tuning.html | 123 +-
userguide/tips/index.html | 123 +-
userguide/tips/mixserver.html | 123 +-
userguide/tips/rand_amplify.html | 123 +-
userguide/tips/rowid.html | 123 +-
userguide/tips/rt_prediction.html | 123 +-
userguide/troubleshooting/asterisk.html | 123 +-
userguide/troubleshooting/index.html | 123 +-
.../troubleshooting/mapjoin_classcastex.html | 123 +-
.../troubleshooting/mapjoin_task_error.html | 123 +-
userguide/troubleshooting/num_mappers.html | 123 +-
userguide/troubleshooting/oom.html | 123 +-
127 files changed, 18424 insertions(+), 5074 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/anomaly/changefinder.html
----------------------------------------------------------------------
diff --git a/userguide/anomaly/changefinder.html b/userguide/anomaly/changefinder.html
index 995d99f..c1a8fa0 100644
--- a/userguide/anomaly/changefinder.html
+++ b/userguide/anomaly/changefinder.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
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- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
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- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2563,7 +2608,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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Random Forest
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<b>7.1.1.</b>
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<b>6.2.2.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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+ Data Preparation
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[05/33] incubator-hivemall-site git commit: Update tutorial for
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<b>6.2.1.</b>
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Logistic Regression
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- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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+ <a href="../../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../../binaryclass/news20_adagrad.html">
+
+ <a href="../../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
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+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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- <a href="../../regression/e2006_arow.html">
+ <a href="../../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../../regression/e2006_arow.html">
+
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+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
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+ a9a Tutorial for DataFrame
</a>
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- E2006-tfidf regression tutorial for DataFrame
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</a>
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- Top-k join processing
+ Top-k Join Processing
</a>
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- <a href="../.." >E2006-tfidf regression tutorial for DataFrame</a>
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<b>6.2.2.</b>
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Logistic Regression
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<b>6.3.4.</b>
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+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <b>6.3.6.</b>
Random Forest
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- Data preparation
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</a>
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- Data preparation
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</a>
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- Data pareparation
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- Data preparation
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</a>
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<b>7.1.1.</b>
- Data preparation
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</a>
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+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</a>
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</a>
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- Data preparation
+ Data Preparation
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+ Item-based Collaborative Filtering
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+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
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</a>
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- E2006-tfidf regression tutorial for SQL
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</a>
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- Generic features
+ Generic Features
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- Top-k join processing
+ Top-k Join Processing
</a>
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</a>
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- <a href="../.." >E2006-tfidf regression tutorial for SQL</a>
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@@ -2517,7 +2562,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/supervised_learning/prediction.html
----------------------------------------------------------------------
diff --git a/userguide/supervised_learning/prediction.html b/userguide/supervised_learning/prediction.html
index 24d1c45..0b86e68 100644
--- a/userguide/supervised_learning/prediction.html
+++ b/userguide/supervised_learning/prediction.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2481,12 +2526,122 @@ E(\mathbf{w}) := \frac{1}{n} \sum_{i=1}^{n} L(\mathbf{w}; \mathbf{x}_i, y_i) + \
<ul>
<li>Optimizer: <code>-opt</code>, <code>-optimizer</code><ul>
<li>SGD</li>
-<li>AdaGrad</li>
-<li>AdaDelta</li>
-<li>Adam</li>
+<li>Momentum<ul>
+<li>Hyperparameters<ul>
+<li><code>-alpha 1.0</code> Learning rate.</li>
+<li><code>-momentum 0.9</code> Exponential decay rate of the first order moment.</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>Nesterov<ul>
+<li>See: <a href="https://arxiv.org/abs/1212.0901" target="_blank">https://arxiv.org/abs/1212.0901</a></li>
+<li>Hyperparameters<ul>
+<li>same as Momentum</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>AdaGrad (default)<ul>
+<li>See: <a href="http://jmlr.org/papers/v12/duchi11a.html" target="_blank">http://jmlr.org/papers/v12/duchi11a.html</a></li>
+<li>Hyperparameters<ul>
+<li><code>-eps 1.0</code> Constant for the numerical stability.</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>RMSprop<ul>
+<li>Description: RMSprop optimizer introducing weight decay to AdaGrad.</li>
+<li>See: <a href="http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf" target="_blank">http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf</a></li>
+<li>Hyperparameters<ul>
+<li><code>-decay 0.95</code> Weight decay rate</li>
+<li><code>-eps 1.0</code> Constant for numerical stability</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>RMSpropGraves<ul>
+<li>Description: Alex Graves's RMSprop introducing weight decay and momentum.</li>
+<li>See: <a href="https://arxiv.org/abs/1308.0850" target="_blank">https://arxiv.org/abs/1308.0850</a></li>
+<li>Hyperparameters<ul>
+<li><code>-alpha 1.0</code> Learning rate.</li>
+<li><code>-decay 0.95</code> Weight decay rate</li>
+<li><code>-momentum 0.9</code> Exponential decay rate of the first order moment.</li>
+<li><code>-eps 1.0</code> Constant for numerical stability</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>AdaDelta<ul>
+<li>See: <a href="https://arxiv.org/abs/1212.5701" target="_blank">https://arxiv.org/abs/1212.5701</a></li>
+<li>Hyperparameters<ul>
+<li><code>-decay 0.95</code> Weight decay rate</li>
+<li><code>-eps 1e-6f</code> Constant for numerical stability</li>
+</ul>
+</li>
</ul>
</li>
+<li>Adam<ul>
+<li>See:<ul>
+<li><a href="https://arxiv.org/abs/1412.6980v8" target="_blank">Adam: A Method for Stochastic Optimization</a></li>
+<li><a href="https://openreview.net/forum?id=rk6qdGgCZ" target="_blank">Fixing Weight Decay Regularization in Adam</a></li>
+<li><a href="https://openreview.net/forum?id=ryQu7f-RZ" target="_blank">On the Convergence of Adam and Beyond</a></li>
</ul>
+</li>
+<li>Hyperparameters<ul>
+<li><code>-alpha 1.0</code> Learning rate.</li>
+<li><code>-beta1 0.9</code> Exponential decay rate of the first order moment.</li>
+<li><code>-beta2 0.999</code> Exponential decay rate of the second order moment.</li>
+<li><code>-eps 1e-8f</code> Constant for numerical stability</li>
+<li><code>-decay 0.0</code> Weight decay rate</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>Nadam<ul>
+<li>Description: Nadam is Adam optimizer with Nesterov momentum.</li>
+<li>See:<ul>
+<li><a href="https://openreview.net/pdf?id=OM0jvwB8jIp57ZJjtNEZ" target="_blank">Incorporating Nesterov Momentum into Adam</a></li>
+<li><a href="http://cs229.stanford.edu/proj2015/054_report.pdf" target="_blank">Adam report</a></li>
+<li><a href="http://www.cs.toronto.edu/~fritz/absps/momentum.pdf" target="_blank">On the importance of initialization and momentum in deep learning</a></li>
+</ul>
+</li>
+<li>Hyperparameters<ul>
+<li>same as Adam except ...</li>
+<li><code>-scheduleDecay 0.004</code> Scheduled decay rate (for each 250 steps by the default; 1/250=0.004)</li>
+</ul>
+</li>
+</ul>
+</li>
+<li>Eve<ul>
+<li>See: <a href="https://openreview.net/forum?id=r1WUqIceg" target="_blank">https://openreview.net/forum?id=r1WUqIceg</a></li>
+<li>Hyperparameters<ul>
+<li>same as Adam except ...</li>
+<li><code>-beta3 0.999</code> Decay rate for Eve coefficient.</li>
+<li><code>-c 10</code> Constant used for gradient clipping <code>clip(val, 1/c, c)</code></li>
+</ul>
+</li>
+</ul>
+</li>
+<li>AdamHD<ul>
+<li>Description: Adam optimizer with Hypergradient Descent. Learning rate <code>-alpha</code> is automatically tuned.</li>
+<li>See:<ul>
+<li><a href="https://openreview.net/forum?id=BkrsAzWAb" target="_blank">Online Learning Rate Adaptation with Hypergradient Descent</a></li>
+<li><a href="https://damaru2.github.io/convergence_analysis_hypergradient_descent/dissertation_hypergradients.pdf" target="_blank">Convergence Analysis of an Adaptive Method of Gradient Descent</a></li>
+</ul>
+</li>
+<li>Hyperparameters<ul>
+<li>same as Adam except ...</li>
+<li><code>-alpha 0.02</code> Learning rate.</li>
+<li><code>-beta -1e-6</code> Constant used for tuning learning rate.</li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+<p>Default (Adagrad+RDA), AdaDelta, Adam, and AdamHD is worth trying in my experience.</p>
<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>Option values are case insensitive and you can use <code>sgd</code> or <code>rda</code>, or <code>huberloss</code> in lower-case letters.</p></div></div>
<p>Furthermore, optimizer offers to set auxiliary options such as:</p>
<ul>
@@ -2506,8 +2661,13 @@ E(\mathbf{w}) := \frac{1}{n} \sum_{i=1}^{n} L(\mathbf{w}; \mathbf{x}_i, y_i) + \
</li>
</ul>
<p>For details of available options, following queries might be helpful to list all of them:</p>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> train_regressor(<span class="hljs-built_in">array</span>(), <span class="hljs-number">0</span>, <span class="hljs-string">'-help'</span>);
-<span class="hljs-keyword">select</span> train_classifier(<span class="hljs-built_in">array</span>(), <span class="hljs-number">0</span>, <span class="hljs-string">'-help'</span>);
+<pre><code class="lang-sql"><span class="hljs-keyword">select</span> train_regressor(<span class="hljs-string">'-help'</span>);
+<span class="hljs-comment">-- v0.5.0 or before</span>
+<span class="hljs-comment">-- select train_regressor(array(), 0, '-help');</span>
+
+<span class="hljs-keyword">select</span> train_classifier(<span class="hljs-string">'-help'</span>);
+<span class="hljs-comment">-- v0.5.0 or before</span>
+<span class="hljs-comment">-- select train_classifier(array(), 0, '-help');</span>
</code></pre>
<p>In practice, you can try different combinations of the options in order to achieve higher prediction accuracy.</p>
<p><div id="page-footer" class="localized-footer"><hr><!--
@@ -2565,7 +2725,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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});
</script>
</div>
@@ -2595,7 +2755,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/supervised_learning/tutorial.html
----------------------------------------------------------------------
diff --git a/userguide/supervised_learning/tutorial.html b/userguide/supervised_learning/tutorial.html
index 67e3a41..559f60a 100644
--- a/userguide/supervised_learning/tutorial.html
+++ b/userguide/supervised_learning/tutorial.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2352,12 +2397,6 @@
training
;
</code></pre>
-<p>Hivemall function <a href="../misc/funcs.html#others"><code>hivemall_version()</code></a> shows current Hivemall version, for example:</p>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> hivemall_version();
-</code></pre>
-<blockquote>
-<p>"0.5.1-incubating-SNAPSHOT"</p>
-</blockquote>
<p>Below we list ML and relevant problems that Hivemall can solve:</p>
<ul>
<li><a href="../binaryclass/general.html">Binary and multi-class classification</a></li>
@@ -2603,7 +2642,9 @@
</table>
<p>Notice that weight is learned for each possible value in a categorical feature, and for every single quantitative feature.</p>
<p>Of course, you can optimize hyper-parameters to build more accurate prediction model. Check the output of the following query to see all available options, including learning rate, number of iterations and regularization parameters, and their default values:</p>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> train_classifier(<span class="hljs-built_in">array</span>(), <span class="hljs-number">0</span>, <span class="hljs-string">'-help'</span>);
+<pre><code class="lang-sql"><span class="hljs-keyword">select</span> train_classifier(<span class="hljs-string">'-help'</span>);
+<span class="hljs-comment">-- Hivemall 0.5.2 and before</span>
+<span class="hljs-comment">-- select train_classifier(array(), 0, '-help');</span>
</code></pre>
<h3 id="step-3-prediction">Step 3. Prediction</h3>
<p>Now, the table <code>classifier</code> has liner coefficients for given features, and we can predict unforeseen samples by computing a weighted sum of their features.</p>
@@ -2625,14 +2666,17 @@
<span class="hljs-comment">-- to join with a model table</span>
extract_feature(fv) <span class="hljs-keyword">as</span> feature,
extract_weight(fv) <span class="hljs-keyword">as</span> <span class="hljs-keyword">value</span>
- <span class="hljs-keyword">from</span> unforeseen_samples t1 LATERAL <span class="hljs-keyword">VIEW</span> explode(features) t2 <span class="hljs-keyword">as</span> fv
+ <span class="hljs-keyword">from</span>
+ unforeseen_samples t1
+ LATERAL <span class="hljs-keyword">VIEW</span> explode(features) t2 <span class="hljs-keyword">as</span> fv
)
<span class="hljs-keyword">select</span>
t1.<span class="hljs-keyword">id</span>,
sigmoid( <span class="hljs-keyword">sum</span>(p1.weight * t1.<span class="hljs-keyword">value</span>) ) <span class="hljs-keyword">as</span> probability
<span class="hljs-keyword">from</span>
features_exploded t1
- <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> classifier p1 <span class="hljs-keyword">ON</span> (t1.feature = p1.feature)
+ <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> classifier p1
+ <span class="hljs-keyword">ON</span> (t1.feature = p1.feature)
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
t1.<span class="hljs-keyword">id</span>
;
@@ -2661,7 +2705,9 @@
<span class="hljs-keyword">id</span>,
extract_feature(fv) <span class="hljs-keyword">as</span> feature,
extract_weight(fv) <span class="hljs-keyword">as</span> <span class="hljs-keyword">value</span>
- <span class="hljs-keyword">from</span> training t1 LATERAL <span class="hljs-keyword">VIEW</span> explode(features) t2 <span class="hljs-keyword">as</span> fv
+ <span class="hljs-keyword">from</span>
+ training t1
+ LATERAL <span class="hljs-keyword">VIEW</span> explode(features) t2 <span class="hljs-keyword">as</span> fv
),
predictions <span class="hljs-keyword">as</span> (
<span class="hljs-keyword">select</span>
@@ -2669,7 +2715,8 @@ predictions <span class="hljs-keyword">as</span> (
sigmoid( <span class="hljs-keyword">sum</span>(p1.weight * t1.<span class="hljs-keyword">value</span>) ) <span class="hljs-keyword">as</span> probability
<span class="hljs-keyword">from</span>
features_exploded t1
- <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> classifier p1 <span class="hljs-keyword">ON</span> (t1.feature = p1.feature)
+ <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> classifier p1
+ <span class="hljs-keyword">ON</span> (t1.feature = p1.feature)
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
t1.<span class="hljs-keyword">id</span>
)
@@ -2677,10 +2724,13 @@ predictions <span class="hljs-keyword">as</span> (
auc(probability, label) <span class="hljs-keyword">as</span> auc,
logloss(probability, label) <span class="hljs-keyword">as</span> logloss
<span class="hljs-keyword">from</span> (
- <span class="hljs-keyword">select</span> t1.probability, t2.label
- <span class="hljs-keyword">from</span> predictions t1
- <span class="hljs-keyword">join</span> training t2 <span class="hljs-keyword">on</span> (t1.<span class="hljs-keyword">id</span> = t2.<span class="hljs-keyword">id</span>)
- <span class="hljs-keyword">ORDER</span> <span class="hljs-keyword">BY</span> probability <span class="hljs-keyword">DESC</span>
+ <span class="hljs-keyword">select</span>
+ t1.probability, t2.label
+ <span class="hljs-keyword">from</span>
+ predictions t1
+ <span class="hljs-keyword">join</span> training t2 <span class="hljs-keyword">on</span> (t1.<span class="hljs-keyword">id</span> = t2.<span class="hljs-keyword">id</span>)
+ <span class="hljs-keyword">ORDER</span> <span class="hljs-keyword">BY</span>
+ probability <span class="hljs-keyword">DESC</span>
) t
;
</code></pre>
@@ -2792,7 +2842,9 @@ predictions <span class="hljs-keyword">as</span> (
</code></pre>
<p><code>-loss_function squared</code> means that this query builds a simple linear regressor with the squared loss. Meanwhile, this example optimizes the parameters based on the <code>AdaGrad</code> optimization scheme with <code>l2</code> regularization.</p>
<p>Run the function with <code>-help</code> option to list available options:</p>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> train_regressor(<span class="hljs-built_in">array</span>(), <span class="hljs-number">0</span>, <span class="hljs-string">'-help'</span>);
+<pre><code class="lang-sql"><span class="hljs-keyword">select</span> train_regressor(<span class="hljs-string">'-help'</span>);
+<span class="hljs-comment">-- Hivemall 0.5.2 and before</span>
+<span class="hljs-comment">-- select train_regressor(array(), 0, '-help');</span>
</code></pre>
<h3 id="step-3-prediction">Step 3. Prediction</h3>
<p>Prepare dummy new customers:</p>
@@ -2844,7 +2896,9 @@ predictions <span class="hljs-keyword">as</span> (
<span class="hljs-keyword">id</span>,
extract_feature(fv) <span class="hljs-keyword">as</span> feature,
extract_weight(fv) <span class="hljs-keyword">as</span> <span class="hljs-keyword">value</span>
- <span class="hljs-keyword">from</span> training t1 LATERAL <span class="hljs-keyword">VIEW</span> explode(features) t2 <span class="hljs-keyword">as</span> fv
+ <span class="hljs-keyword">from</span>
+ training t1
+ LATERAL <span class="hljs-keyword">VIEW</span> explode(features) t2 <span class="hljs-keyword">as</span> fv
),
predictions <span class="hljs-keyword">as</span> (
<span class="hljs-keyword">select</span>
@@ -2943,7 +2997,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[16/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/multiclass/iris_randomforest.html
----------------------------------------------------------------------
diff --git a/userguide/multiclass/iris_randomforest.html b/userguide/multiclass/iris_randomforest.html
index 2ed3106..e5bf9e1 100644
--- a/userguide/multiclass/iris_randomforest.html
+++ b/userguide/multiclass/iris_randomforest.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
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+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2733,7 +2778,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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diff --git a/userguide/multiclass/iris_scw.html b/userguide/multiclass/iris_scw.html
index ddcabfe..b86bac4 100644
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+++ b/userguide/multiclass/iris_scw.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
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+
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+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
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<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
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+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.3.1.</b>
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index b58589f..e243635 100644
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<b>6.2.1.</b>
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<b>6.2.2.</b>
+ General Binary Classifier
+
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+
+
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Logistic Regression
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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Random Forest
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+ Data Preparation
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<b>6.5.1.</b>
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+ Data Preparation
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<b>6.6.1.</b>
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+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
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<b>8.2.2.</b>
+ General Regessor
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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- Data preparation
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<b>6.2.2.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.5.1.</b>
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<b>7.1.2.</b>
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</a>
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<b>8.2.2.</b>
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+ Data Preparation
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<b>6.2.1.</b>
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<b>6.2.2.</b>
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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+
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AdaGradRDA, AdaGrad, AdaDelta
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
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</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
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+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>8.2.2.</b>
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+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</a>
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<b>9.3.1.</b>
- Data preparation
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</a>
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+ gitbook.page.hasChanged({"page":{"title":"Ensemble learning","level":"7.1.5","depth":2,"next":{"title":"one-vs-the-rest Classifier","level":"7.1.6","depth":2,"path":"multiclass/news20_one-vs-the-rest.md","ref":"multiclass/news20_one-vs-the-rest.md","articles":[]},"previous":{"title":"CW, AROW, SCW","level":"7.1.4","depth":2,"path":"multiclass/news20_scw.md","ref":"multiclass/news20_scw.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/
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});
</script>
</div>
@@ -2594,7 +2639,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[25/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/news20_pa.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/news20_pa.html b/userguide/binaryclass/news20_pa.html
index b13456e..1dcd198 100644
--- a/userguide/binaryclass/news20_pa.html
+++ b/userguide/binaryclass/news20_pa.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2317,12 +2362,6 @@
specific language governing permissions and limitations
under the License.
-->
-<h2 id="udf-preparation">UDF preparation</h2>
-<pre><code>delete jar /home/myui/tmp/hivemall.jar;
-add jar /home/myui/tmp/hivemall.jar;
-
-source /home/myui/tmp/define-all.hive;
-</code></pre><hr>
<h1 id="perceptron">[Perceptron]</h1>
<h2 id="model-building">model building</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_perceptron_model1;
@@ -2332,7 +2371,7 @@ source /home/myui/tmp/define-all.hive;
voted_avg(weight) <span class="hljs-keyword">as</span> weight
<span class="hljs-keyword">from</span>
(<span class="hljs-keyword">select</span>
- perceptron(add_bias(features),label) <span class="hljs-keyword">as</span> (feature,weight)
+ train_perceptron(add_bias(features),label) <span class="hljs-keyword">as</span> (feature,weight)
<span class="hljs-keyword">from</span>
news20b_train_x3
) t
@@ -2355,23 +2394,19 @@ source /home/myui/tmp/define-all.hive;
<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_perceptron_submit1 <span class="hljs-keyword">as</span>
<span class="hljs-keyword">select</span>
t.label <span class="hljs-keyword">as</span> actual,
- pd.label <span class="hljs-keyword">as</span> predicted
+ p.label <span class="hljs-keyword">as</span> predicted
<span class="hljs-keyword">from</span>
- news20b_test t <span class="hljs-keyword">JOIN</span> news20b_perceptron_predict1 pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
+ news20b_test t <span class="hljs-keyword">JOIN</span> news20b_perceptron_predict1 p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>);
</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_perceptron_submit1
-<span class="hljs-keyword">where</span> actual == predicted;
+<pre><code class="lang-sql"><span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ news20b_perceptron_submit1;
</code></pre>
<blockquote>
<p>0.9459567654123299</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_perceptron_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_perceptron_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_perceptron_submit1;
-</code></pre>
-<hr>
<h1 id="passive-aggressive">[Passive Aggressive]</h1>
<h2 id="model-building">model building</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_pa_model1;
@@ -2408,18 +2443,14 @@ select
from
news20b_test t JOIN news20b_pa_predict1 pd
on (t.rowid = pd.rowid);
-</code></pre><pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_pa_submit1
-<span class="hljs-keyword">where</span> actual == predicted;
+</code></pre><pre><code class="lang-sql"><span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ news20b_pa_submit1;
</code></pre>
<blockquote>
<p>0.9603682946357086</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_pa_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_pa_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_pa_submit1;
-</code></pre>
-<hr>
<h1 id="passive-aggressive-pa1">[Passive Aggressive (PA1)]</h1>
<h2 id="model-building">model building</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_pa1_model1;
@@ -2443,8 +2474,9 @@ from
<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>) <span class="hljs-keyword">as</span> total_weight,
<span class="hljs-keyword">case</span> <span class="hljs-keyword">when</span> <span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>) > <span class="hljs-number">0.0</span> <span class="hljs-keyword">then</span> <span class="hljs-number">1</span> <span class="hljs-keyword">else</span> <span class="hljs-number">-1</span> <span class="hljs-keyword">end</span> <span class="hljs-keyword">as</span> label
<span class="hljs-keyword">from</span>
- news20b_test_exploded t <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span>
- news20b_pa1_model1 m <span class="hljs-keyword">ON</span> (t.feature = m.feature)
+ news20b_test_exploded t
+ <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> news20b_pa1_model1 m
+ <span class="hljs-keyword">ON</span> (t.feature = m.feature)
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
@@ -2452,23 +2484,20 @@ from
<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_pa1_submit1 <span class="hljs-keyword">as</span>
<span class="hljs-keyword">select</span>
t.label <span class="hljs-keyword">as</span> actual,
- pd.label <span class="hljs-keyword">as</span> predicted
+ p.label <span class="hljs-keyword">as</span> predicted
<span class="hljs-keyword">from</span>
- news20b_test t <span class="hljs-keyword">JOIN</span> news20b_pa1_predict1 pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
+ news20b_test t
+ <span class="hljs-keyword">JOIN</span> news20b_pa1_predict1 p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>);
</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_pa1_submit1
-<span class="hljs-keyword">where</span> actual == predicted;
+<pre><code class="lang-sql"><span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ news20b_pa1_submit1;
</code></pre>
<blockquote>
<p>0.9601681345076061</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_pa1_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_pa1_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_pa1_submit1;
-</code></pre>
-<hr>
<h1 id="passive-aggressive-pa2">[Passive Aggressive (PA2)]</h1>
<h2 id="model-building">model building</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_pa2_model1;
@@ -2506,17 +2535,14 @@ from
news20b_test t <span class="hljs-keyword">JOIN</span> news20b_pa2_predict1 pd
<span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_pa2_submit1
-<span class="hljs-keyword">where</span> actual == predicted;
+<pre><code class="lang-sql"><span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ news20b_pa2_submit1;
</code></pre>
<blockquote>
<p>0.9597678142514011</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_pa2_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_pa2_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_pa2_submit1;
-</code></pre>
<p><div id="page-footer" class="localized-footer"><hr><!--
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
@@ -2572,7 +2598,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
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@@ -2602,7 +2628,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
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index e859b4e..f65a2e2 100644
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+++ b/userguide/binaryclass/news20_rf.html
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<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <li class="chapter active" data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2317,9 +2362,9 @@
specific language governing permissions and limitations
under the License.
-->
-<p>Hivemall Random Forest supports libsvm-like sparse inputs. </p>
-<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>This feature, i.e., Sparse input support in Random Forest, is supported since Hivemall v0.5.0 or later._
-<a href="https://hivemall.incubator.apache.org/userguide/ft_engineering/hashing.html#featurehashing-function" target="_blank"><code>feature_hashing</code></a> function is useful to prepare feature vectors for Random Forest.</p></div></div>
+<p>Hivemall Random Forest supports libsvm-like sparse inputs. This page shows a classification example on 20-newsgroup dataset.</p>
+<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>This feature, i.e., Sparse input support in Random Forest, is supported since Hivemall v0.5.0 or later.
+<a href="http://hivemall.incubator.apache.org/userguide/ft_engineering/hashing.html#featurehashing-function" target="_blank"><code>feature_hashing</code></a> function is useful to prepare feature vectors for Random Forest.</p></div></div>
<!-- toc --><div id="toc" class="toc">
<ul>
@@ -2441,7 +2486,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2471,7 +2516,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
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@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
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- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
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- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
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+
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+
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+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2317,13 +2362,6 @@
specific language governing permissions and limitations
under the License.
-->
-<h2 id="udf-preparation">UDF preparation</h2>
-<pre><code>use news20;
-
-delete jar /home/myui/tmp/hivemall.jar;
-add jar /home/myui/tmp/hivemall.jar;
-source /home/myui/tmp/define-all.hive;
-</code></pre><hr>
<h1 id="confidece-weighted-cw">Confidece Weighted (CW)</h1>
<h2 id="training">training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_cw_model1;
@@ -2355,28 +2393,22 @@ source /home/myui/tmp/define-all.hive;
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_cw_submit1
-<span class="hljs-keyword">as</span>
+<pre><code class="lang-sql">WITH submit as (
<span class="hljs-keyword">select</span>
t.<span class="hljs-keyword">rowid</span>,
t.label <span class="hljs-keyword">as</span> actual,
- pd.label <span class="hljs-keyword">as</span> predicted
+ p.label <span class="hljs-keyword">as</span> predicted
<span class="hljs-keyword">from</span>
- news20b_test t <span class="hljs-keyword">JOIN</span> news20b_cw_predict1 pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
-</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_cw_submit1
-<span class="hljs-keyword">where</span> actual = predicted;
+ news20b_test t
+ <span class="hljs-keyword">JOIN</span> news20b_cw_predict1 p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
+<span class="hljs-keyword">select</span> <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span> submit;
</code></pre>
<blockquote>
<p>0.9655724579663731</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_cw_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_cw_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_cw_submit1;
-</code></pre>
-<hr>
<h1 id="adaptive-regularization-of-weight-vectors-arow">Adaptive Regularization of Weight Vectors (AROW)</h1>
<h2 id="training">training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_arow_model1;
@@ -2408,27 +2440,22 @@ source /home/myui/tmp/define-all.hive;
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_arow_submit1 <span class="hljs-keyword">as</span>
-<span class="hljs-keyword">select</span>
+<pre><code class="lang-sql">WITH submit as (
+<span class="hljs-keyword">select</span>
t.<span class="hljs-keyword">rowid</span>,
t.label <span class="hljs-keyword">as</span> actual,
- pd.label <span class="hljs-keyword">as</span> predicted
+ p.label <span class="hljs-keyword">as</span> predicted
<span class="hljs-keyword">from</span>
- news20b_test t <span class="hljs-keyword">JOIN</span> news20b_arow_predict1 pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
-</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_arow_submit1
-<span class="hljs-keyword">where</span> actual = predicted;
+ news20b_test t
+ <span class="hljs-keyword">JOIN</span> news20b_arow_predict1 p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
+<span class="hljs-keyword">select</span> <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span> submit;
</code></pre>
<blockquote>
<p>0.9659727782225781</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_arow_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_arow_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_arow_submit1;
-</code></pre>
-<hr>
<h1 id="soft-confidence-weighted-scw1">Soft Confidence-Weighted (SCW1)</h1>
<h2 id="training">training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_scw_model1;
@@ -2460,27 +2487,21 @@ source /home/myui/tmp/define-all.hive;
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_scw_submit1 <span class="hljs-keyword">as</span>
-<span class="hljs-keyword">select</span>
- t.<span class="hljs-keyword">rowid</span>,
- t.label <span class="hljs-keyword">as</span> actual,
- pd.label <span class="hljs-keyword">as</span> predicted
-<span class="hljs-keyword">from</span>
- news20b_test t <span class="hljs-keyword">JOIN</span> news20b_scw_predict1 pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
-</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_scw_submit1
-<span class="hljs-keyword">where</span> actual = predicted;
+<pre><code class="lang-sql">WITH submit as (
+ <span class="hljs-keyword">select</span>
+ t.<span class="hljs-keyword">rowid</span>,
+ t.label <span class="hljs-keyword">as</span> actual,
+ p.label <span class="hljs-keyword">as</span> predicted
+ <span class="hljs-keyword">from</span>
+ news20b_test t <span class="hljs-keyword">JOIN</span> news20b_scw_predict1 p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
+<span class="hljs-keyword">select</span> <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span> submit
</code></pre>
<blockquote>
<p>0.9661729383506805</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_scw_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_scw_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_scw_submit1;
-</code></pre>
-<hr>
<h1 id="soft-confidence-weighted-scw2">Soft Confidence-Weighted (SCW2)</h1>
<h2 id="training">training</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_scw2_model1;
@@ -2512,26 +2533,22 @@ source /home/myui/tmp/define-all.hive;
t.<span class="hljs-keyword">rowid</span>;
</code></pre>
<h2 id="evaluation">evaluation</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_scw2_submit1 <span class="hljs-keyword">as</span>
+<pre><code class="lang-sql">WITH submit as (
<span class="hljs-keyword">select</span>
t.<span class="hljs-keyword">rowid</span>,
t.label <span class="hljs-keyword">as</span> actual,
pd.label <span class="hljs-keyword">as</span> predicted
<span class="hljs-keyword">from</span>
- news20b_test t <span class="hljs-keyword">JOIN</span> news20b_scw2_predict1 pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>);
-</code></pre>
-<pre><code class="lang-sql"><span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>)/<span class="hljs-number">4996</span> <span class="hljs-keyword">from</span> news20b_scw2_submit1
-<span class="hljs-keyword">where</span> actual = predicted;
+ news20b_test t
+ <span class="hljs-keyword">JOIN</span> news20b_scw2_predict1 pd
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>)
+)
+<span class="hljs-keyword">select</span> <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span> submit;
</code></pre>
<blockquote>
<p>0.9579663730984788</p>
</blockquote>
-<h2 id="cleaning">Cleaning</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_scw2_model1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_scw2_predict1;
-<span class="hljs-keyword">drop</span> <span class="hljs-keyword">view</span> news20b_scw2_submit1;
-</code></pre>
<p>--</p>
<table>
<thead>
@@ -2631,7 +2648,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"CW, AROW, SCW","level":"6.3.3","depth":2,"next":{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.3.4","depth":2,"path":"binaryclass/news20_adagrad.md","ref":"binaryclass/news20_adagrad.md","articles":[]},"previous":{"title":"Perceptron, Passive Aggressive","level":"6.3.2","depth":2,"path":"binaryclass/news20_pa.md","ref":"binaryclass/news20_pa.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apach
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+ gitbook.page.hasChanged({"page":{"title":"CW, AROW, SCW","level":"6.3.3","depth":2,"next":{"title":"General Binary Classifier","level":"6.3.4","depth":2,"path":"binaryclass/news20_generic.md","ref":"binaryclass/news20_generic.md","articles":[]},"previous":{"title":"Perceptron, Passive Aggressive","level":"6.3.2","depth":2,"path":"binaryclass/news20_pa.md","ref":"binaryclass/news20_pa.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/in
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});
</script>
</div>
@@ -2661,7 +2678,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[28/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/kdd2010a_scw.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/kdd2010a_scw.html b/userguide/binaryclass/kdd2010a_scw.html
index e254123..a4b8d7e 100644
--- a/userguide/binaryclass/kdd2010a_scw.html
+++ b/userguide/binaryclass/kdd2010a_scw.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
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<b>6.5.1.</b>
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<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
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<b>13.2.2.</b>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >Data preparation</a>
+ <a href=".." >Data Preparation</a>
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@@ -2456,7 +2501,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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----------------------------------------------------------------------
diff --git a/userguide/binaryclass/news20.html b/userguide/binaryclass/news20.html
index 741d2f2..3d0eda2 100644
--- a/userguide/binaryclass/news20.html
+++ b/userguide/binaryclass/news20.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
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- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
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+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
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- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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[15/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/multiclass/news20_one-vs-the-rest.html
----------------------------------------------------------------------
diff --git a/userguide/multiclass/news20_one-vs-the-rest.html b/userguide/multiclass/news20_one-vs-the-rest.html
index b9e5dc7..5e8ea0c 100644
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<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>one-vs-the-rest classifier · Hivemall User Manual</title>
+ <title>one-vs-the-rest Classifier · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
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<b>6.2.1.</b>
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+ Data Preparation
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@@ -980,13 +980,28 @@
</li>
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="../binaryclass/a9a_minibatch.html">
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+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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<b>6.3.4.</b>
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+
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+ <a href="../binaryclass/news20_adagrad.html">
+
+
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
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+ Data Preparation
</a>
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<b>6.6.1.</b>
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+ Data Preparation for one-vs-the-rest classifiers
</a>
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+ one-vs-the-rest Classifier
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
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+
+
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+ Data Preparation
</a>
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+ Data Preparation
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+ LSH/MinHash and Jaccard Similarity
</a>
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+ 10-fold Cross Validation (Matrix Factorization)
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../binaryclass/news20_rf.html">
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Random Forest
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<b>7.1.1.</b>
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</a>
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- <a href=".." >Data preparation for one-vs-the-rest classifiers</a>
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<b>6.2.1.</b>
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<b>6.3.4.</b>
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
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</a>
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<b>6.6.1.</b>
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</a>
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<b>6.8.1.</b>
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</a>
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<b>7.1.1.</b>
- Data preparation
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</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
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<b>8.2.2.</b>
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</a>
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<b>9.2.1.</b>
- Data preparation
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</a>
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</a>
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+ a9a Tutorial for DataFrame
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<b>6.2.2.</b>
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Logistic Regression
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+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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+ <b>6.3.6.</b>
Random Forest
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</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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</a>
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<b>8.2.2.</b>
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</a>
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- LSH/MinHash and brute-force search
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</a>
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- Data preparation
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
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- 10-fold cross validation (Matrix Factorization)
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</a>
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- E2006-tfidf regression tutorial for DataFrame
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- E2006-tfidf regression tutorial for SQL
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- Generic features
+ Generic Features
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- Top-k join processing
+ Top-k Join Processing
</a>
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index ce55df6..fbe4935 100644
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<b>6.2.1.</b>
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</a>
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<b>6.2.2.</b>
+ General Binary Classifier
+
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+
+
+
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+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
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Logistic Regression
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+ Mini-batch Gradient Descent
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<b>6.3.1.</b>
- Data preparation
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<b>6.3.4.</b>
+ General Binary Classifier
+
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+
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+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
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+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
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<b>8.2.2.</b>
+ General Regessor
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+
+
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+
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+
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+
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
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+ LSH/MinHash and Jaccard Similarity
</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
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+ SLIM for fast top-k Recommendation
</a>
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+ 10-fold Cross Validation (Matrix Factorization)
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
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- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
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+ Other Utility Functions
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[21/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/ft_engineering/bm25.html
----------------------------------------------------------------------
diff --git a/userguide/ft_engineering/bm25.html b/userguide/ft_engineering/bm25.html
index 4269d94..6215747 100644
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<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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<b>6.3.4.</b>
+ General Binary Classifier
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+
+
+
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+
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+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
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+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
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+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
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</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
- a9a tutorial for SQL
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</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
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</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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@@ -2598,7 +2643,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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index ddc7807..3fb5918 100644
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@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
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+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
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+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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+ Generic Features
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- Top-k join processing
+ Top-k Join Processing
</a>
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- Other utility functions
+ Other Utility Functions
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index b8fd4c1..8359cc5 100644
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<b>6.2.1.</b>
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</a>
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</li>
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<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
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+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2483,7 +2528,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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----------------------------------------------------------------------
diff --git a/userguide/ft_engineering/pairing.html b/userguide/ft_engineering/pairing.html
index e16b442..540c359 100644
--- a/userguide/ft_engineering/pairing.html
+++ b/userguide/ft_engineering/pairing.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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<b>6.2.2.</b>
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Logistic Regression
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.5.1.</b>
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</a>
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<b>6.6.1.</b>
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<b>6.8.1.</b>
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</a>
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<b>7.1.1.</b>
- Data preparation
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<b>7.1.2.</b>
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+ LSH/MinHash and Brute-force Search
</a>
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<b>13.3.1.</b>
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
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+ Top-k Join Processing
</a>
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[30/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/a9a_lr.html
----------------------------------------------------------------------
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Logistic Regression
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<b>6.3.4.</b>
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<b>6.5.1.</b>
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Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2317,6 +2362,8 @@
specific language governing permissions and limitations
under the License.
-->
+<p>This pages shows an example of applying logistic regression for a9a binary classification task.</p>
+<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p><code>logloss()</code> became deprecated since v0.5.0 release. Use smarter <a href="a9a_generic.html">general classifier</a> instead.</p></div></div>
<!-- toc --><div id="toc" class="toc">
<ul>
@@ -2349,7 +2396,7 @@
) t
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature;
</code></pre>
-<p><em>"-total_steps" option is optional for logress() function.</em><br><em>I recommend you NOT to use options (e.g., total_steps and eta0) if you are not familiar with those options. Hivemall then uses an autonomic ETA (learning rate) estimator.</em></p>
+<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p><code>-total_steps</code> option is optional for logress() function. We recommend you NOT to use options (e.g., <code>total_steps</code> and <code>eta0</code>) if you are not familiar with those options. Hivemall then uses an autonomic ETA (learning rate) estimator.</p></div></div>
<h1 id="prediction">prediction</h1>
<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> a9a_predict1
<span class="hljs-keyword">as</span>
@@ -2443,7 +2490,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ gitbook.page.hasChanged({"page":{"title":"Logistic Regression","level":"6.2.3","depth":2,"next":{"title":"Mini-batch Gradient Descent","level":"6.2.4","depth":2,"path":"binaryclass/a9a_minibatch.md","ref":"binaryclass/a9a_minibatch.md","articles":[]},"previous":{"title":"General Binary Classifier","level":"6.2.2","depth":2,"path":"binaryclass/a9a_generic.md","ref":"binaryclass/a9a_generic.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apac
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</script>
</div>
@@ -2473,7 +2520,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/a9a_minibatch.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/a9a_minibatch.html b/userguide/binaryclass/a9a_minibatch.html
index 7554705..7e33ddc 100644
--- a/userguide/binaryclass/a9a_minibatch.html
+++ b/userguide/binaryclass/a9a_minibatch.html
@@ -4,7 +4,7 @@
<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>Mini-batch gradient descent · Hivemall User Manual</title>
+ <title>Mini-batch Gradient Descent · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter active" data-level="6.2.3" data-path="a9a_minibatch.html">
+ <li class="chapter active" data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >Mini-batch gradient descent</a>
+ <a href=".." >Mini-batch Gradient Descent</a>
</h1>
</div>
@@ -2317,8 +2362,16 @@
specific language governing permissions and limitations
under the License.
-->
-<p>This page explains how to apply <a href="https://class.coursera.org/ml-003/lecture/106" target="_blank">Mini-Batch Gradient Descent</a> for the training of logistic regression explained in <a href="a9a_lr.html">this example</a>.
-So, refer <a href="a9a_lr.html">this page</a> first. This content depends on it.</p>
+<p>This page explains how to apply <a href="https://class.coursera.org/ml-003/lecture/106" target="_blank">Mini-Batch Gradient Descent</a> for the training of logistic regression explained in <a href="a9a_lr.html">this example</a>. So, refer <a href="a9a_lr.html">this page</a> first. This content depends on it.</p>
+<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p><code>logloss()</code> became deprecated since v0.5.0 release. Use smarter <a href="a9a_generic.html">general classifier</a> instead. You can use <code>-mini_batch</code> option in general classifier as well.</p></div></div>
+<!-- toc --><div id="toc" class="toc">
+
+<ul>
+<li><a href="#training">Training</a></li>
+<li><a href="#evaluation">Evaluation</a></li>
+</ul>
+
+</div><!-- tocstop -->
<h1 id="training">Training</h1>
<p>Replace <code>a9a_model1</code> of <a href="a9a_lr.html">this example</a>.</p>
<pre><code class="lang-sql"><span class="hljs-keyword">set</span> hivevar:total_steps=<span class="hljs-number">32561</span>;
@@ -2410,7 +2463,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
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+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
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<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >Data preparation</a>
+ <a href=".." >Data Preparation</a>
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@@ -2435,7 +2480,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2465,7 +2510,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[09/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/regression/kddcup12tr2.html
----------------------------------------------------------------------
diff --git a/userguide/regression/kddcup12tr2.html b/userguide/regression/kddcup12tr2.html
index f38dc94..05052c5 100644
--- a/userguide/regression/kddcup12tr2.html
+++ b/userguide/regression/kddcup12tr2.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="e2006_generic.html">
- <a href="e2006_arow.html">
+ <a href="e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2402,7 +2447,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
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----------------------------------------------------------------------
diff --git a/userguide/regression/kddcup12tr2_adagrad.html b/userguide/regression/kddcup12tr2_adagrad.html
index 923864f..d9260ee 100644
--- a/userguide/regression/kddcup12tr2_adagrad.html
+++ b/userguide/regression/kddcup12tr2_adagrad.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
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</li>
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
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</a>
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</li>
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+ <a href="e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
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</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
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<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
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+ Top-k Join Processing
</a>
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<b>13.4.2.</b>
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<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
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<b>6.2.1.</b>
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</li>
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<b>6.2.2.</b>
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+
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+
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+
Logistic Regression
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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</a>
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<b>8.2.1.</b>
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</a>
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</li>
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<b>8.2.2.</b>
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+ </a>
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+
+
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+
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+
+
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+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
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- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
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</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
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</a>
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- E2006-tfidf regression tutorial for SQL
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</a>
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<b>13.4.</b>
- Generic features
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- Top-k join processing
+ Top-k Join Processing
</a>
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</a>
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Random Forest
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="e2006_generic.html">
- <a href="e2006_arow.html">
+ <a href="e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2466,7 +2511,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2496,7 +2541,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[32/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/a9a_dataset.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/a9a_dataset.html b/userguide/binaryclass/a9a_dataset.html
index 089f049..72293c2 100644
--- a/userguide/binaryclass/a9a_dataset.html
+++ b/userguide/binaryclass/a9a_dataset.html
@@ -4,7 +4,7 @@
<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>Data preparation · Hivemall User Manual</title>
+ <title>Data Preparation · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
@@ -97,7 +97,7 @@
<link rel="shortcut icon" href="../gitbook/images/favicon.ico" type="image/x-icon">
- <link rel="next" href="a9a_lr.html" />
+ <link rel="next" href="a9a_generic.html" />
<link rel="prev" href="a9a.html" />
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >Data preparation</a>
+ <a href=".." >Data Preparation</a>
</h1>
</div>
@@ -2402,7 +2447,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2432,7 +2477,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[02/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/troubleshooting/asterisk.html
----------------------------------------------------------------------
diff --git a/userguide/troubleshooting/asterisk.html b/userguide/troubleshooting/asterisk.html
index 61ab3c7..e346ef7 100644
--- a/userguide/troubleshooting/asterisk.html
+++ b/userguide/troubleshooting/asterisk.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2374,7 +2419,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2404,7 +2449,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/troubleshooting/index.html
----------------------------------------------------------------------
diff --git a/userguide/troubleshooting/index.html b/userguide/troubleshooting/index.html
index f5f70de..44fe3b9 100644
--- a/userguide/troubleshooting/index.html
+++ b/userguide/troubleshooting/index.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
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Random Forest
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<b>6.2.2.</b>
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2376,7 +2421,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2406,7 +2451,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/troubleshooting/num_mappers.html
----------------------------------------------------------------------
diff --git a/userguide/troubleshooting/num_mappers.html b/userguide/troubleshooting/num_mappers.html
index 415627f..33b0865 100644
--- a/userguide/troubleshooting/num_mappers.html
+++ b/userguide/troubleshooting/num_mappers.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2384,7 +2429,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
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@@ -2414,7 +2459,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[04/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/tips/addbias.html
----------------------------------------------------------------------
diff --git a/userguide/tips/addbias.html b/userguide/tips/addbias.html
index 02078f9..1a1e7ad 100644
--- a/userguide/tips/addbias.html
+++ b/userguide/tips/addbias.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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</a>
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<b>6.3.1.</b>
- Data preparation
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<b>6.3.4.</b>
+ General Binary Classifier
+
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+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
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</a>
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</li>
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<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
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+
+
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Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
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</a>
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</a>
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</a>
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</a>
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<b>13.2.1.</b>
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</a>
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</a>
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</a>
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<b>6.2.2.</b>
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Logistic Regression
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
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</a>
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<b>6.3.4.</b>
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+
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AdaGradRDA, AdaGrad, AdaDelta
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
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<b>8.2.2.</b>
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+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ LSH/MinHash and Brute-force Search
</a>
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- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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</a>
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- 10-fold cross validation (Matrix Factorization)
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</a>
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</a>
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</a>
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</a>
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+ Top-k Join Processing
</a>
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Random Forest
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<b>8.2.2.</b>
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</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
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<b>9.2.2.</b>
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+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
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+ SLIM for fast top-k Recommendation
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<b>13.2.1.</b>
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</a>
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<b>13.3.1.</b>
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diff --git a/userguide/tips/hadoop_tuning.html b/userguide/tips/hadoop_tuning.html
index 7af1194..2b08f13 100644
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<b>6.2.1.</b>
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<b>6.2.2.</b>
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+
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Logistic Regression
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.5.1.</b>
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<b>6.6.1.</b>
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</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
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<b>8.2.1.</b>
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<b>8.2.2.</b>
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@@ -2471,7 +2516,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[23/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/clustering/plsa.html
----------------------------------------------------------------------
diff --git a/userguide/clustering/plsa.html b/userguide/clustering/plsa.html
index 1fb87f7..6604468 100644
--- a/userguide/clustering/plsa.html
+++ b/userguide/clustering/plsa.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2621,7 +2666,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2651,7 +2696,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/docker/getting_started.html
----------------------------------------------------------------------
diff --git a/userguide/docker/getting_started.html b/userguide/docker/getting_started.html
index 2bca613..a127dcd 100644
--- a/userguide/docker/getting_started.html
+++ b/userguide/docker/getting_started.html
@@ -970,7 +970,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -978,13 +978,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -993,14 +1008,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1036,7 +1051,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1074,13 +1089,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1089,12 +1119,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1132,7 +1162,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1183,7 +1213,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1234,7 +1264,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1300,7 +1330,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1358,7 +1388,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1373,7 +1403,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1433,7 +1463,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1557,7 +1587,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1565,13 +1595,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1608,7 +1653,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1696,7 +1741,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1732,7 +1777,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1747,7 +1792,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1762,7 +1807,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1813,7 +1858,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1828,7 +1873,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1873,7 +1918,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1888,7 +1933,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2078,7 +2123,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2093,7 +2138,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2129,7 +2174,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2144,7 +2189,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2164,7 +2209,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2180,7 +2225,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2195,7 +2240,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2464,7 +2509,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
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Random Forest
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<b>6.5.1.</b>
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</a>
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<b>6.6.1.</b>
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</a>
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<b>6.8.1.</b>
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</a>
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<b>7.1.1.</b>
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+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
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+ Other Utility Functions
</a>
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@@ -2601,7 +2646,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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----------------------------------------------------------------------
diff --git a/userguide/eval/datagen.html b/userguide/eval/datagen.html
index 9aea0ad..9540269 100644
--- a/userguide/eval/datagen.html
+++ b/userguide/eval/datagen.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
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[13/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/recommend/movielens_dataset.html
----------------------------------------------------------------------
diff --git a/userguide/recommend/movielens_dataset.html b/userguide/recommend/movielens_dataset.html
index 459071f..bd81419 100644
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<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>Data preparation · Hivemall User Manual</title>
+ <title>Data Preparation · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
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+
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.5.1.</b>
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</a>
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<b>6.8.1.</b>
- Data preparation
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</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
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</a>
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<b>8.2.1.</b>
- Data preparation
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<b>8.2.2.</b>
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+
+
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+
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Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
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</a>
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<b>9.2.1.</b>
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</a>
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</a>
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</a>
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<b>9.3.5.</b>
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<b>6.2.1.</b>
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<b>6.2.2.</b>
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Logistic Regression
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
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+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
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</a>
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<b>7.1.1.</b>
- Data preparation
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</a>
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</a>
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</a>
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<b>9.2.1.</b>
- Data preparation
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</a>
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</a>
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- Data preparation
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</a>
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</a>
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</a>
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- 10-fold cross validation (Matrix Factorization)
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</a>
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<b>6.2.1.</b>
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<b>6.2.2.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
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</a>
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<b>6.8.1.</b>
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</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
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</a>
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<b>8.2.1.</b>
- Data preparation
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</a>
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</li>
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<b>8.2.2.</b>
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Passive Aggressive, AROW
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- Data preparation
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</a>
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<b>9.1.1.</b>
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+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
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</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
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</a>
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</a>
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</a>
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+ Generic Features
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+ Top-k Join Processing
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<b>6.2.2.</b>
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Logistic Regression
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<b>6.3.4.</b>
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Random Forest
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<b>8.2.2.</b>
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</a>
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+ Data Preparation
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<b>9.2.2.</b>
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+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
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- SLIM for fast top-k recommendation
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- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
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<b>13.2.1.</b>
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
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<b>13.4.2.</b>
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+ Other Utility Functions
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<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >SLIM for fast top-k recommendation</a>
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index 2f996f6..4eb2598 100644
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+++ b/userguide/recommend/news20.html
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<b>6.2.1.</b>
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</a>
@@ -980,13 +980,28 @@
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
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+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
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+
Logistic Regression
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+ Mini-batch Gradient Descent
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
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+
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+
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+
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+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
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+
+
+
+ </li>
+
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+
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+
+
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+
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
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+ LSH/MinHash and Jaccard Similarity
</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
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+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
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+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
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+ a9a Tutorial for DataFrame
</a>
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+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
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@@ -2182,7 +2227,7 @@
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- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
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[03/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/tips/index.html
----------------------------------------------------------------------
diff --git a/userguide/tips/index.html b/userguide/tips/index.html
index 5458f71..55c7494 100644
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<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
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+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
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+
+
+
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+
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+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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@@ -1076,13 +1091,28 @@
</li>
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
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- <a href="../regression/e2006_arow.html">
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<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
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</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
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<b>13.4.2.</b>
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----------------------------------------------------------------------
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index bc3daa1..c9a00bd 100644
--- a/userguide/tips/mixserver.html
+++ b/userguide/tips/mixserver.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
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+
+ <a href="../binaryclass/a9a_lr.html">
+
+
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+
Logistic Regression
</a>
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
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+
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+
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+
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+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
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<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
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- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
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- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
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- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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Random Forest
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</a>
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<b>6.5.1.</b>
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<b>6.6.1.</b>
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<b>6.8.1.</b>
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</a>
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<b>7.1.1.</b>
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<b>6.2.2.</b>
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Logistic Regression
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Random Forest
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</a>
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<b>6.5.1.</b>
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</a>
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<b>7.1.1.</b>
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</a>
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<b>8.2.2.</b>
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</a>
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+ Item-based Collaborative Filtering
</a>
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</a>
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----------------------------------------------------------------------
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index 5fe3519..619f801 100644
--- a/userguide/tips/rt_prediction.html
+++ b/userguide/tips/rt_prediction.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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</li>
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
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+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
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</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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[10/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/regression/e2006_generic.html
----------------------------------------------------------------------
diff --git a/userguide/regression/e2006_generic.html b/userguide/regression/e2006_generic.html
new file mode 100644
index 0000000..c309e93
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+
+
+ <b>1.1.</b>
+
+ Introduction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2" data-path="../getting_started/">
+
+ <a href="../getting_started/">
+
+
+ <b>1.2.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.2.1" data-path="../getting_started/installation.html">
+
+ <a href="../getting_started/installation.html">
+
+
+ <b>1.2.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.2" data-path="../getting_started/permanent-functions.html">
+
+ <a href="../getting_started/permanent-functions.html">
+
+
+ <b>1.2.2.</b>
+
+ Install as permanent functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.3" data-path="../getting_started/input-format.html">
+
+ <a href="../getting_started/input-format.html">
+
+
+ <b>1.2.3.</b>
+
+ Input Format
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.3" data-path="../misc/funcs.html">
+
+ <a href="../misc/funcs.html">
+
+
+ <b>1.3.</b>
+
+ List of Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4" data-path="../tips/">
+
+ <a href="../tips/">
+
+
+ <b>1.4.</b>
+
+ Tips for Effective Hivemall
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.4.1" data-path="../tips/addbias.html">
+
+ <a href="../tips/addbias.html">
+
+
+ <b>1.4.1.</b>
+
+ Explicit add_bias() for better prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.2" data-path="../tips/rand_amplify.html">
+
+ <a href="../tips/rand_amplify.html">
+
+
+ <b>1.4.2.</b>
+
+ Use rand_amplify() to better prediction results
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.3" data-path="../tips/rt_prediction.html">
+
+ <a href="../tips/rt_prediction.html">
+
+
+ <b>1.4.3.</b>
+
+ Real-time prediction on RDBMS
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.4" data-path="../tips/ensemble_learning.html">
+
+ <a href="../tips/ensemble_learning.html">
+
+
+ <b>1.4.4.</b>
+
+ Ensemble learning for stable prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.5" data-path="../tips/mixserver.html">
+
+ <a href="../tips/mixserver.html">
+
+
+ <b>1.4.5.</b>
+
+ Mixing models for a better prediction convergence (MIX server)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.6" data-path="../tips/emr.html">
+
+ <a href="../tips/emr.html">
+
+
+ <b>1.4.6.</b>
+
+ Run Hivemall on Amazon Elastic MapReduce
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.5" data-path="../tips/general_tips.html">
+
+ <a href="../tips/general_tips.html">
+
+
+ <b>1.5.</b>
+
+ General Hive/Hadoop Tips
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.5.1" data-path="../tips/rowid.html">
+
+ <a href="../tips/rowid.html">
+
+
+ <b>1.5.1.</b>
+
+ Adding rowid for each row
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.5.2" data-path="../tips/hadoop_tuning.html">
+
+ <a href="../tips/hadoop_tuning.html">
+
+
+ <b>1.5.2.</b>
+
+ Hadoop tuning for Hivemall
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.6" data-path="../troubleshooting/">
+
+ <a href="../troubleshooting/">
+
+
+ <b>1.6.</b>
+
+ Troubleshooting
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.6.1" data-path="../troubleshooting/oom.html">
+
+ <a href="../troubleshooting/oom.html">
+
+
+ <b>1.6.1.</b>
+
+ OutOfMemoryError in training
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.2" data-path="../troubleshooting/mapjoin_task_error.html">
+
+ <a href="../troubleshooting/mapjoin_task_error.html">
+
+
+ <b>1.6.2.</b>
+
+ SemanticException generate map join task error: Cannot serialize object
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.3" data-path="../troubleshooting/asterisk.html">
+
+ <a href="../troubleshooting/asterisk.html">
+
+
+ <b>1.6.3.</b>
+
+ Asterisk argument for UDTF does not work
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.4" data-path="../troubleshooting/num_mappers.html">
+
+ <a href="../troubleshooting/num_mappers.html">
+
+
+ <b>1.6.4.</b>
+
+ The number of mappers is less than input splits in Hadoop 2.x
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.5" data-path="../troubleshooting/mapjoin_classcastex.html">
+
+ <a href="../troubleshooting/mapjoin_classcastex.html">
+
+
+ <b>1.6.5.</b>
+
+ Map-side join causes ClassCastException on Tez
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part II - Generic Features</li>
+
+
+
+ <li class="chapter " data-level="2.1" data-path="../misc/generic_funcs.html">
+
+ <a href="../misc/generic_funcs.html">
+
+
+ <b>2.1.</b>
+
+ List of Generic Hivemall Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.2" data-path="../misc/topk.html">
+
+ <a href="../misc/topk.html">
+
+
+ <b>2.2.</b>
+
+ Efficient Top-K Query Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.3" data-path="../misc/tokenizer.html">
+
+ <a href="../misc/tokenizer.html">
+
+
+ <b>2.3.</b>
+
+ Text Tokenizer
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.4" data-path="../misc/approx.html">
+
+ <a href="../misc/approx.html">
+
+
+ <b>2.4.</b>
+
+ Approximate Aggregate Functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part III - Feature Engineering</li>
+
+
+
+ <li class="chapter " data-level="3.1" data-path="../ft_engineering/scaling.html">
+
+ <a href="../ft_engineering/scaling.html">
+
+
+ <b>3.1.</b>
+
+ Feature Scaling
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.2" data-path="../ft_engineering/hashing.html">
+
+ <a href="../ft_engineering/hashing.html">
+
+
+ <b>3.2.</b>
+
+ Feature Hashing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.3" data-path="../ft_engineering/selection.html">
+
+ <a href="../ft_engineering/selection.html">
+
+
+ <b>3.3.</b>
+
+ Feature Selection
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.4" data-path="../ft_engineering/binning.html">
+
+ <a href="../ft_engineering/binning.html">
+
+
+ <b>3.4.</b>
+
+ Feature Binning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.5" data-path="../ft_engineering/pairing.html">
+
+ <a href="../ft_engineering/pairing.html">
+
+
+ <b>3.5.</b>
+
+ Feature Paring
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.5.1" data-path="../ft_engineering/polynomial.html">
+
+ <a href="../ft_engineering/polynomial.html">
+
+
+ <b>3.5.1.</b>
+
+ Polynomial features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.6" data-path="../ft_engineering/ft_trans.html">
+
+ <a href="../ft_engineering/ft_trans.html">
+
+
+ <b>3.6.</b>
+
+ Feature Transformation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.6.1" data-path="../ft_engineering/vectorization.html">
+
+ <a href="../ft_engineering/vectorization.html">
+
+
+ <b>3.6.1.</b>
+
+ Feature vectorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.6.2" data-path="../ft_engineering/quantify.html">
+
+ <a href="../ft_engineering/quantify.html">
+
+
+ <b>3.6.2.</b>
+
+ Quantify non-number features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.7" data-path="../ft_engineering/term_vector.html">
+
+ <a href="../ft_engineering/term_vector.html">
+
+
+ <b>3.7.</b>
+
+ Term Vector Model
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.7.1" data-path="../ft_engineering/tfidf.html">
+
+ <a href="../ft_engineering/tfidf.html">
+
+
+ <b>3.7.1.</b>
+
+ TF-IDF Term Weighting
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.7.2" data-path="../ft_engineering/bm25.html">
+
+ <a href="../ft_engineering/bm25.html">
+
+
+ <b>3.7.2.</b>
+
+ Okapi BM25 Term Weighting
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IV - Evaluation</li>
+
+
+
+ <li class="chapter " data-level="4.1" data-path="../eval/binary_classification_measures.html">
+
+ <a href="../eval/binary_classification_measures.html">
+
+
+ <b>4.1.</b>
+
+ Binary Classification Metrics
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.1.1" data-path="../eval/auc.html">
+
+ <a href="../eval/auc.html">
+
+
+ <b>4.1.1.</b>
+
+ Area under the ROC curve
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="4.2" data-path="../eval/multilabel_classification_measures.html">
+
+ <a href="../eval/multilabel_classification_measures.html">
+
+
+ <b>4.2.</b>
+
+ Multi-label Classification Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.3" data-path="../eval/regression.html">
+
+ <a href="../eval/regression.html">
+
+
+ <b>4.3.</b>
+
+ Regression Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.4" data-path="../eval/rank.html">
+
+ <a href="../eval/rank.html">
+
+
+ <b>4.4.</b>
+
+ Ranking Measures
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.5" data-path="../eval/datagen.html">
+
+ <a href="../eval/datagen.html">
+
+
+ <b>4.5.</b>
+
+ Data Generation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.5.1" data-path="../eval/lr_datagen.html">
+
+ <a href="../eval/lr_datagen.html">
+
+
+ <b>4.5.1.</b>
+
+ Logistic Regression data generation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part V - Supervised Learning</li>
+
+
+
+ <li class="chapter " data-level="5.1" data-path="../supervised_learning/prediction.html">
+
+ <a href="../supervised_learning/prediction.html">
+
+
+ <b>5.1.</b>
+
+ How Prediction Works
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="5.2" data-path="../supervised_learning/tutorial.html">
+
+ <a href="../supervised_learning/tutorial.html">
+
+
+ <b>5.2.</b>
+
+ Step-by-Step Tutorial on Supervised Learning
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part VI - Binary Classification</li>
+
+
+
+ <li class="chapter " data-level="6.1" data-path="../binaryclass/general.html">
+
+ <a href="../binaryclass/general.html">
+
+
+ <b>6.1.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2" data-path="../binaryclass/a9a.html">
+
+ <a href="../binaryclass/a9a.html">
+
+
+ <b>6.2.</b>
+
+ a9a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.2.1" data-path="../binaryclass/a9a_dataset.html">
+
+ <a href="../binaryclass/a9a_dataset.html">
+
+
+ <b>6.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
+
+ <a href="../binaryclass/a9a_generic.html">
+
+
+ <b>6.2.2.</b>
+
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
+ Logistic Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
+
+ <a href="../binaryclass/a9a_minibatch.html">
+
+
+ <b>6.2.4.</b>
+
+ Mini-batch Gradient Descent
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.3" data-path="../binaryclass/news20.html">
+
+ <a href="../binaryclass/news20.html">
+
+
+ <b>6.3.</b>
+
+ News20 Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.3.1" data-path="../binaryclass/news20_dataset.html">
+
+ <a href="../binaryclass/news20_dataset.html">
+
+
+ <b>6.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.2" data-path="../binaryclass/news20_pa.html">
+
+ <a href="../binaryclass/news20_pa.html">
+
+
+ <b>6.3.2.</b>
+
+ Perceptron, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.3" data-path="../binaryclass/news20_scw.html">
+
+ <a href="../binaryclass/news20_scw.html">
+
+
+ <b>6.3.3.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
+
+ <a href="../binaryclass/news20_generic.html">
+
+
+ <b>6.3.4.</b>
+
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
+ AdaGradRDA, AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
+
+ <a href="../binaryclass/news20_rf.html">
+
+
+ <b>6.3.6.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.4" data-path="../binaryclass/kdd2010a.html">
+
+ <a href="../binaryclass/kdd2010a.html">
+
+
+ <b>6.4.</b>
+
+ KDD2010a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.4.1" data-path="../binaryclass/kdd2010a_dataset.html">
+
+ <a href="../binaryclass/kdd2010a_dataset.html">
+
+
+ <b>6.4.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.4.2" data-path="../binaryclass/kdd2010a_scw.html">
+
+ <a href="../binaryclass/kdd2010a_scw.html">
+
+
+ <b>6.4.2.</b>
+
+ PA, CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.5" data-path="../binaryclass/kdd2010b.html">
+
+ <a href="../binaryclass/kdd2010b.html">
+
+
+ <b>6.5.</b>
+
+ KDD2010b Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.5.1" data-path="../binaryclass/kdd2010b_dataset.html">
+
+ <a href="../binaryclass/kdd2010b_dataset.html">
+
+
+ <b>6.5.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.5.2" data-path="../binaryclass/kdd2010b_arow.html">
+
+ <a href="../binaryclass/kdd2010b_arow.html">
+
+
+ <b>6.5.2.</b>
+
+ AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.6" data-path="../binaryclass/webspam.html">
+
+ <a href="../binaryclass/webspam.html">
+
+
+ <b>6.6.</b>
+
+ Webspam Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.6.1" data-path="../binaryclass/webspam_dataset.html">
+
+ <a href="../binaryclass/webspam_dataset.html">
+
+
+ <b>6.6.1.</b>
+
+ Data Pareparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.6.2" data-path="../binaryclass/webspam_scw.html">
+
+ <a href="../binaryclass/webspam_scw.html">
+
+
+ <b>6.6.2.</b>
+
+ PA1, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.7" data-path="../binaryclass/titanic_rf.html">
+
+ <a href="../binaryclass/titanic_rf.html">
+
+
+ <b>6.7.</b>
+
+ Kaggle Titanic Tutorial
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8" data-path="../binaryclass/criteo.html">
+
+ <a href="../binaryclass/criteo.html">
+
+
+ <b>6.8.</b>
+
+ Criteo Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.8.1" data-path="../binaryclass/criteo_dataset.html">
+
+ <a href="../binaryclass/criteo_dataset.html">
+
+
+ <b>6.8.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8.2" data-path="../binaryclass/criteo_ffm.html">
+
+ <a href="../binaryclass/criteo_ffm.html">
+
+
+ <b>6.8.2.</b>
+
+ Field-Aware Factorization Machines
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VII - Multiclass Classification</li>
+
+
+
+ <li class="chapter " data-level="7.1" data-path="../multiclass/news20.html">
+
+ <a href="../multiclass/news20.html">
+
+
+ <b>7.1.</b>
+
+ News20 Multiclass Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.1.1" data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>7.1.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.2" data-path="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+
+ <b>7.1.2.</b>
+
+ Data Preparation for one-vs-the-rest classifiers
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.3" data-path="../multiclass/news20_pa.html">
+
+ <a href="../multiclass/news20_pa.html">
+
+
+ <b>7.1.3.</b>
+
+ PA
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.4" data-path="../multiclass/news20_scw.html">
+
+ <a href="../multiclass/news20_scw.html">
+
+
+ <b>7.1.4.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.5" data-path="../multiclass/news20_ensemble.html">
+
+ <a href="../multiclass/news20_ensemble.html">
+
+
+ <b>7.1.5.</b>
+
+ Ensemble learning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.6" data-path="../multiclass/news20_one-vs-the-rest.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest.html">
+
+
+ <b>7.1.6.</b>
+
+ one-vs-the-rest Classifier
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="7.2" data-path="../multiclass/iris.html">
+
+ <a href="../multiclass/iris.html">
+
+
+ <b>7.2.</b>
+
+ Iris Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.2.1" data-path="../multiclass/iris_dataset.html">
+
+ <a href="../multiclass/iris_dataset.html">
+
+
+ <b>7.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.2" data-path="../multiclass/iris_scw.html">
+
+ <a href="../multiclass/iris_scw.html">
+
+
+ <b>7.2.2.</b>
+
+ SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.3" data-path="../multiclass/iris_randomforest.html">
+
+ <a href="../multiclass/iris_randomforest.html">
+
+
+ <b>7.2.3.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VIII - Regression</li>
+
+
+
+ <li class="chapter " data-level="8.1" data-path="general.html">
+
+ <a href="general.html">
+
+
+ <b>8.1.</b>
+
+ Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2" data-path="e2006.html">
+
+ <a href="e2006.html">
+
+
+ <b>8.2.</b>
+
+ E2006-tfidf Regression Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.2.1" data-path="e2006_dataset.html">
+
+ <a href="e2006_dataset.html">
+
+
+ <b>8.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter active" data-level="8.2.2" data-path="e2006_generic.html">
+
+ <a href="e2006_generic.html">
+
+
+ <b>8.2.2.</b>
+
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
+ Passive Aggressive, AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="8.3" data-path="kddcup12tr2.html">
+
+ <a href="kddcup12tr2.html">
+
+
+ <b>8.3.</b>
+
+ KDDCup 2012 Track 2 CTR Prediction Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.3.1" data-path="kddcup12tr2_dataset.html">
+
+ <a href="kddcup12tr2_dataset.html">
+
+
+ <b>8.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.2" data-path="kddcup12tr2_lr.html">
+
+ <a href="kddcup12tr2_lr.html">
+
+
+ <b>8.3.2.</b>
+
+ Logistic Regression, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.3" data-path="kddcup12tr2_lr_amplify.html">
+
+ <a href="kddcup12tr2_lr_amplify.html">
+
+
+ <b>8.3.3.</b>
+
+ Logistic Regression with amplifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.4" data-path="kddcup12tr2_adagrad.html">
+
+ <a href="kddcup12tr2_adagrad.html">
+
+
+ <b>8.3.4.</b>
+
+ AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IX - Recommendation</li>
+
+
+
+ <li class="chapter " data-level="9.1" data-path="../recommend/cf.html">
+
+ <a href="../recommend/cf.html">
+
+
+ <b>9.1.</b>
+
+ Collaborative Filtering
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.1.1" data-path="../recommend/item_based_cf.html">
+
+ <a href="../recommend/item_based_cf.html">
+
+
+ <b>9.1.1.</b>
+
+ Item-based Collaborative Filtering
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.2" data-path="../recommend/news20.html">
+
+ <a href="../recommend/news20.html">
+
+
+ <b>9.2.</b>
+
+ News20 Related Article Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.2.1" data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>9.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.2" data-path="../recommend/news20_jaccard.html">
+
+ <a href="../recommend/news20_jaccard.html">
+
+
+ <b>9.2.2.</b>
+
+ LSH/MinHash and Jaccard Similarity
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.3" data-path="../recommend/news20_knn.html">
+
+ <a href="../recommend/news20_knn.html">
+
+
+ <b>9.2.3.</b>
+
+ LSH/MinHash and Brute-force Search
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.4" data-path="../recommend/news20_bbit_minhash.html">
+
+ <a href="../recommend/news20_bbit_minhash.html">
+
+
+ <b>9.2.4.</b>
+
+ kNN search using b-Bits MinHash
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.3" data-path="../recommend/movielens.html">
+
+ <a href="../recommend/movielens.html">
+
+
+ <b>9.3.</b>
+
+ MovieLens Movie Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.3.1" data-path="../recommend/movielens_dataset.html">
+
+ <a href="../recommend/movielens_dataset.html">
+
+
+ <b>9.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.2" data-path="../recommend/movielens_cf.html">
+
+ <a href="../recommend/movielens_cf.html">
+
+
+ <b>9.3.2.</b>
+
+ Item-based Collaborative Filtering
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.3" data-path="../recommend/movielens_mf.html">
+
+ <a href="../recommend/movielens_mf.html">
+
+
+ <b>9.3.3.</b>
+
+ Matrix Factorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.4" data-path="../recommend/movielens_fm.html">
+
+ <a href="../recommend/movielens_fm.html">
+
+
+ <b>9.3.4.</b>
+
+ Factorization Machine
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.5" data-path="../recommend/movielens_slim.html">
+
+ <a href="../recommend/movielens_slim.html">
+
+
+ <b>9.3.5.</b>
+
+ SLIM for fast top-k Recommendation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.6" data-path="../recommend/movielens_cv.html">
+
+ <a href="../recommend/movielens_cv.html">
+
+
+ <b>9.3.6.</b>
+
+ 10-fold Cross Validation (Matrix Factorization)
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part X - Anomaly Detection</li>
+
+
+
+ <li class="chapter " data-level="10.1" data-path="../anomaly/lof.html">
+
+ <a href="../anomaly/lof.html">
+
+
+ <b>10.1.</b>
+
+ Outlier Detection using Local Outlier Factor (LOF)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.2" data-path="../anomaly/sst.html">
+
+ <a href="../anomaly/sst.html">
+
+
+ <b>10.2.</b>
+
+ Change-Point Detection using Singular Spectrum Transformation (SST)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.3" data-path="../anomaly/changefinder.html">
+
+ <a href="../anomaly/changefinder.html">
+
+
+ <b>10.3.</b>
+
+ ChangeFinder: Detecting Outlier and Change-Point Simultaneously
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XI - Clustering</li>
+
+
+
+ <li class="chapter " data-level="11.1" data-path="../clustering/lda.html">
+
+ <a href="../clustering/lda.html">
+
+
+ <b>11.1.</b>
+
+ Latent Dirichlet Allocation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="11.2" data-path="../clustering/plsa.html">
+
+ <a href="../clustering/plsa.html">
+
+
+ <b>11.2.</b>
+
+ Probabilistic Latent Semantic Analysis
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XII - GeoSpatial Functions</li>
+
+
+
+ <li class="chapter " data-level="12.1" data-path="../geospatial/latlon.html">
+
+ <a href="../geospatial/latlon.html">
+
+
+ <b>12.1.</b>
+
+ Lat/Lon functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIII - Hivemall on Spark</li>
+
+
+
+ <li class="chapter " data-level="13.1" data-path="../spark/getting_started/">
+
+ <a href="../spark/getting_started/">
+
+
+ <b>13.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.1.1" data-path="../spark/getting_started/installation.html">
+
+ <a href="../spark/getting_started/installation.html">
+
+
+ <b>13.1.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.2" data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.2.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.2.1" data-path="../spark/binaryclass/a9a_df.html">
+
+ <a href="../spark/binaryclass/a9a_df.html">
+
+
+ <b>13.2.1.</b>
+
+ a9a Tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.2.2" data-path="../spark/binaryclass/a9a_sql.html">
+
+ <a href="../spark/binaryclass/a9a_sql.html">
+
+
+ <b>13.2.2.</b>
+
+ a9a Tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.3" data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.3.</b>
+
+ Regression
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.3.1" data-path="../spark/regression/e2006_df.html">
+
+ <a href="../spark/regression/e2006_df.html">
+
+
+ <b>13.3.1.</b>
+
+ E2006-tfidf Regression Tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.3.2" data-path="../spark/regression/e2006_sql.html">
+
+ <a href="../spark/regression/e2006_sql.html">
+
+
+ <b>13.3.2.</b>
+
+ E2006-tfidf Regression Tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.4" data-path="../spark/misc/misc.html">
+
+ <a href="../spark/misc/misc.html">
+
+
+ <b>13.4.</b>
+
+ Generic Features
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.4.1" data-path="../spark/misc/topk_join.html">
+
+ <a href="../spark/misc/topk_join.html">
+
+
+ <b>13.4.1.</b>
+
+ Top-k Join Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.4.2" data-path="../spark/misc/functions.html">
+
+ <a href="../spark/misc/functions.html">
+
+
+ <b>13.4.2.</b>
+
+ Other Utility Functions
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - Hivemall on Docker</li>
+
+
+
+ <li class="chapter " data-level="14.1" data-path="../docker/getting_started.html">
+
+ <a href="../docker/getting_started.html">
+
+
+ <b>14.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - External References</li>
+
+
+
+ <li class="chapter " data-level="15.1" >
+
+ <a target="_blank" href="https://github.com/daijyc/hivemall/wiki/PigHome">
+
+
+ <b>15.1.</b>
+
+ Hivemall on Apache Pig
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+ <li>
+ <a href="https://www.gitbook.com" target="blank" class="gitbook-link">
+ Published with GitBook
+ </a>
+ </li>
+</ul>
+
+
+ </nav>
+
+
+ </div>
+
+ <div class="book-body">
+
+ <div class="body-inner">
+
+
+
+<div class="book-header" role="navigation">
+
+
+ <!-- Title -->
+ <h1>
+ <i class="fa fa-circle-o-notch fa-spin"></i>
+ <a href=".." >General Regessor</a>
+ </h1>
+</div>
+
+
+
+
+ <div class="page-wrapper" tabindex="-1" role="main">
+ <div class="page-inner">
+
+<div id="book-search-results">
+ <div class="search-noresults">
+
+ <section class="normal markdown-section">
+
+ <!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<p>This tutorial shows how to apply General Regressor for a regression problem of e2006 dataset.</p>
+<!-- toc --><div id="toc" class="toc">
+
+<ul>
+<li><a href="#training">Training</a></li>
+<li><a href="#prediction">prediction</a></li>
+<li><a href="#evaluation">evaluation</a></li>
+</ul>
+
+</div><!-- tocstop -->
+<h2 id="training">Training</h2>
+<pre><code class="lang-sql"><span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">32</span>;
+
+<span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> e2006tfidf_generic_model;
+<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> e2006tfidf_generic_model <span class="hljs-keyword">as</span>
+<span class="hljs-keyword">select</span>
+ feature,
+ <span class="hljs-keyword">avg</span>(weight) <span class="hljs-keyword">as</span> weight
+<span class="hljs-keyword">from</span>
+ (<span class="hljs-keyword">select</span>
+ train_regressor(
+ add_bias(features), target,
+ <span class="hljs-string">'-loss squaredloss -opt AdamHD -reg No -iters 20'</span>
+ ) <span class="hljs-keyword">as</span> (feature, weight)
+ <span class="hljs-keyword">from</span>
+ e2006tfidf_train_x3
+ ) t
+<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature;
+
+<span class="hljs-comment">-- reset to the default setting</span>
+<span class="hljs-keyword">set</span> mapred.reduce.tasks=<span class="hljs-number">-1</span>;
+</code></pre>
+<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p>Regularization could not work well for regression problem. Then, try providing <code>-reg No</code> option as seen in the above query.
+Also, do not use <code>voted_avg()</code> for regression. <code>voted_avg()</code> is for classification.</p></div></div>
+<h2 id="prediction">prediction</h2>
+<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> e2006tfidf_generic_predict
+<span class="hljs-keyword">as</span>
+<span class="hljs-keyword">select</span>
+ t.<span class="hljs-keyword">rowid</span>,
+ <span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>) <span class="hljs-keyword">as</span> predicted
+<span class="hljs-keyword">from</span>
+ e2006tfidf_test_exploded t <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span>
+ e2006tfidf_generic_model m <span class="hljs-keyword">ON</span> (t.feature = m.feature)
+<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
+ t.<span class="hljs-keyword">rowid</span>;
+</code></pre>
+<h2 id="evaluation">evaluation</h2>
+<pre><code class="lang-sql">WITH submit as (
+ <span class="hljs-keyword">select</span>
+ t.target <span class="hljs-keyword">as</span> actual,
+ p.predicted <span class="hljs-keyword">as</span> predicted
+ <span class="hljs-keyword">from</span>
+ e2006tfidf_test t
+ <span class="hljs-keyword">JOIN</span> e2006tfidf_generic_predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
+<span class="hljs-keyword">select</span>
+ rmse(predicted, actual) <span class="hljs-keyword">as</span> RMSE,
+ mse(predicted, actual) <span class="hljs-keyword">as</span> MSE,
+ mae(predicted, actual) <span class="hljs-keyword">as</span> MAE,
+ r2(predicted, actual) <span class="hljs-keyword">as</span> R2
+<span class="hljs-keyword">from</span>
+ submit;
+</code></pre>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">rmse</th>
+<th style="text-align:center">mse</th>
+<th style="text-align:center">mae</th>
+<th style="text-align:center">r2</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">0.37125069279938866</td>
+<td style="text-align:center">0.13782707690402607</td>
+<td style="text-align:center">0.2270351090214029</td>
+<td style="text-align:center">0.5232372408076887</td>
+</tr>
+</tbody>
+</table>
+<p><div id="page-footer" class="localized-footer"><hr><!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<p><sub><font color="gray">
+Apache Hivemall is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator.
+</font></sub></p>
+</div></p>
+
+
+ </section>
+
+ </div>
+ <div class="search-results">
+ <div class="has-results">
+
+ <h1 class="search-results-title"><span class='search-results-count'></span> results matching "<span class='search-query'></span>"</h1>
+ <ul class="search-results-list"></ul>
+
+ </div>
+ <div class="no-results">
+
+ <h1 class="search-results-title">No results matching "<span class='search-query'></span>"</h1>
+
+ </div>
+ </div>
+</div>
+
+ </div>
+ </div>
+
+ </div>
+
+
+
+
+ </div>
+
+ <script>
+ var gitbook = gitbook || [];
+ gitbook.push(function() {
+ gitbook.page.hasChanged({"page":{"title":"General Regessor","level":"8.2.2","depth":2,"next":{"title":"Passive Aggressive, AROW","level":"8.2.3","depth":2,"path":"regression/e2006_arow.md","ref":"regression/e2006_arow.md","articles":[]},"previous":{"title":"Data Preparation","level":"8.2.1","depth":2,"path":"regression/e2006_dataset.md","ref":"regression/e2006_dataset.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall
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+ });
+ </script>
+</div>
+
+
+ <script src="../gitbook/gitbook.js"></script>
+ <script src="../gitbook/theme.js"></script>
+
+
+ <script src="../gitbook/gitbook-plugin-edit-link/plugin.js"></script>
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+ <script src="../gitbook/gitbook-plugin-github/plugin.js"></script>
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+
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+ <script src="../gitbook/gitbook-plugin-toggle-chapters/toggle.js"></script>
+
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+
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
+
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor-style.js"></script>
+
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+ <script src="../gitbook/gitbook-plugin-expandable-chapters/expandable-chapters.js"></script>
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+ <script src="../gitbook/gitbook-plugin-search/search-engine.js"></script>
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+ <script src="../gitbook/gitbook-plugin-sharing/buttons.js"></script>
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+ <script src="../gitbook/gitbook-plugin-fontsettings/fontsettings.js"></script>
+
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+
+ <script src="../gitbook/gitbook-plugin-theme-api/theme-api.js"></script>
+
+
+
+ </body>
+</html>
+
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/regression/general.html
----------------------------------------------------------------------
diff --git a/userguide/regression/general.html b/userguide/regression/general.html
index d0d8afc..f5f7ee9 100644
--- a/userguide/regression/general.html
+++ b/userguide/regression/general.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="e2006_generic.html">
- <a href="e2006_arow.html">
+ <a href="e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="e2006_arow.html">
+
+ <a href="e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2424,7 +2469,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
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@@ -2454,7 +2499,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[17/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/misc/generic_funcs.html
----------------------------------------------------------------------
diff --git a/userguide/misc/generic_funcs.html b/userguide/misc/generic_funcs.html
index d8c56e4..1d1a0a6 100644
--- a/userguide/misc/generic_funcs.html
+++ b/userguide/misc/generic_funcs.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
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<a href="../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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----------------------------------------------------------------------
diff --git a/userguide/misc/tokenizer.html b/userguide/misc/tokenizer.html
index 7176b62..c67017f 100644
--- a/userguide/misc/tokenizer.html
+++ b/userguide/misc/tokenizer.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
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- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2444,7 +2489,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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<b>6.2.2.</b>
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Random Forest
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</a>
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<b>7.1.1.</b>
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</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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<b>6.2.1.</b>
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+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
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+
+
+
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+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
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+
+
+ <b>6.2.3.</b>
+
Logistic Regression
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@@ -995,14 +1010,14 @@
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+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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@@ -1076,13 +1091,28 @@
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
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+
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+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
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- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2488,7 +2533,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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[14/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/recommend/item_based_cf.html
----------------------------------------------------------------------
diff --git a/userguide/recommend/item_based_cf.html b/userguide/recommend/item_based_cf.html
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<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
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<b>6.2.1.</b>
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<b>6.2.2.</b>
+ General Binary Classifier
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+
+
+
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+
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+
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+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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<b>6.3.1.</b>
- Data preparation
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
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+
+
+
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+
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+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
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+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
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- Data preparation
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
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+ </a>
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+
+
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+
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+
+ <b>8.2.3.</b>
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Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
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+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
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</a>
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<b>13.3.1.</b>
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+ E2006-tfidf Regression Tutorial for DataFrame
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+ E2006-tfidf Regression Tutorial for SQL
</a>
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- Generic features
+ Generic Features
</a>
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- Top-k join processing
+ Top-k Join Processing
</a>
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index 787b730..e9cf582 100644
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<b>6.2.1.</b>
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<b>6.2.2.</b>
+ General Binary Classifier
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+
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Logistic Regression
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+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
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+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
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+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
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+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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- LSH/MinHash and brute-force search
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</a>
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<b>9.3.1.</b>
- Data preparation
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</a>
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<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
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<b>6.2.1.</b>
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</a>
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<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
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- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
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</a>
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
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+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
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<b>9.3.1.</b>
- Data preparation
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</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
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<b>13.3.1.</b>
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+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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- E2006-tfidf regression tutorial for SQL
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</a>
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+ Generic Features
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- Top-k join processing
+ Top-k Join Processing
</a>
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<b>13.4.2.</b>
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+ Other Utility Functions
</a>
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<h1>
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<b>6.2.2.</b>
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Logistic Regression
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- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
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<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
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+ </a>
+
+
+
+ </li>
+
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+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >10-fold cross validation (Matrix Factorization)</a>
+ <a href=".." >10-fold Cross Validation (Matrix Factorization)</a>
</h1>
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@@ -2423,7 +2468,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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[24/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/titanic_rf.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/titanic_rf.html b/userguide/binaryclass/titanic_rf.html
index 89098d7..d09d031 100644
--- a/userguide/binaryclass/titanic_rf.html
+++ b/userguide/binaryclass/titanic_rf.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
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- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
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+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
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Logistic Regression
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+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
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+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
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+
+
+
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+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
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+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
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+
+
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+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
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</a>
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<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
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+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
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+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
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+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
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+ Data Preparation
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<b>6.3.4.</b>
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+
+ <a href="news20_adagrad.html">
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AdaGradRDA, AdaGrad, AdaDelta
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<a href="news20_rf.html">
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Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
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</a>
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<b>6.6.1.</b>
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</a>
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<b>6.8.1.</b>
- Data preparation
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</a>
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<b>7.1.1.</b>
- Data preparation
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<b>7.1.2.</b>
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<b>8.2.1.</b>
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<b>8.2.2.</b>
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+
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Passive Aggressive, AROW
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<b>9.1.1.</b>
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<b>9.2.1.</b>
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<b>9.3.1.</b>
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<b>13.2.1.</b>
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Logistic Regression
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Random Forest
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<b>6.5.1.</b>
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<b>6.6.1.</b>
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<b>7.1.1.</b>
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<b>8.2.2.</b>
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Passive Aggressive, AROW
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</a>
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<b>9.2.1.</b>
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@@ -2666,7 +2711,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2696,7 +2741,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[29/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/criteo_ffm.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/criteo_ffm.html b/userguide/binaryclass/criteo_ffm.html
index 465f74d..b83faf0 100644
--- a/userguide/binaryclass/criteo_ffm.html
+++ b/userguide/binaryclass/criteo_ffm.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
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+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
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+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2669,7 +2714,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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----------------------------------------------------------------------
diff --git a/userguide/binaryclass/general.html b/userguide/binaryclass/general.html
index c940a38..45c5aa8 100644
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+++ b/userguide/binaryclass/general.html
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<b>6.2.2.</b>
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Logistic Regression
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- Mini-batch gradient descent
+ Mini-batch Gradient Descent
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
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<b>6.3.4.</b>
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AdaGradRDA, AdaGrad, AdaDelta
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</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2317,12 +2362,11 @@
specific language governing permissions and limitations
under the License.
-->
-<p>Hivemall has a generic function for classification: <code>train_classifier</code>. Compared to the other functions we will see in the later chapters, <code>train_classifier</code> provides simpler and configureable generic interface which can be utilized to build binary classification models in a variety of settings.</p>
+<p>Hivemall has a generic function for classification: <code>train_classifier</code>. Compared to the other functions we will see in the later chapters, <code>train_classifier</code> provides simpler and configurable generic interface which can be utilized to build binary classification models in a variety of settings.</p>
<p>Here, we briefly introduce usage of the function. Before trying sample queries, you first need to prepare <a href="https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html#a9a" target="_blank">a9a data</a>. See <a href="a9a_dataset.html">our a9a tutorial page</a> for further instructions.</p>
<!-- toc --><div id="toc" class="toc">
<ul>
-<li><a href="#preparation">Preparation</a></li>
<li><a href="#training">Training</a></li>
<li><a href="#prediction--evaluation">Prediction & evaluation</a></li>
<li><a href="#comparison-with-the-other-binary-classifiers">Comparison with the other binary classifiers</a></li>
@@ -2330,15 +2374,6 @@
</div><!-- tocstop -->
<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>This feature is supported from Hivemall v0.5-rc.1 or later.</p></div></div>
-<h1 id="preparation">Preparation</h1>
-<ul>
-<li>Set <code>total_steps</code> ideally be <code>count(1) / {# of map tasks}</code>:<pre><code> hive> select count(1) from a9a_train;
- hive> set hivevar:total_steps=32561;
-</code></pre></li>
-<li>Set <code>n_samples</code> to compute accuracy of prediction:<pre><code> hive> select count(1) from a9a_test;
- hive> set hivevar:n_samples=16281;
-</code></pre></li>
-</ul>
<h1 id="training">Training</h1>
<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> classification_model <span class="hljs-keyword">as</span>
<span class="hljs-keyword">select</span>
@@ -2347,13 +2382,12 @@
<span class="hljs-keyword">from</span>
(
<span class="hljs-keyword">select</span>
- train_classifier(add_bias(features), label, <span class="hljs-string">'-loss logloss -opt SGD -reg no -eta simple -total_steps ${total_steps}'</span>) <span class="hljs-keyword">as</span> (feature, weight)
+ train_classifier(add_bias(features), label, <span class="hljs-string">'-loss logloss -opt SGD -reg no'</span>) <span class="hljs-keyword">as</span> (feature, weight)
<span class="hljs-keyword">from</span>
a9a_train
) t
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature;
</code></pre>
-<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p><code>-total_steps</code> option is an optional parameter and training works without it.</p></div></div>
<h1 id="prediction--evaluation">Prediction & evaluation</h1>
<pre><code class="lang-sql">WITH test_exploded as (
<span class="hljs-keyword">select</span>
@@ -2370,23 +2404,39 @@ predict <span class="hljs-keyword">as</span> (
sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) <span class="hljs-keyword">as</span> prob,
(<span class="hljs-keyword">case</span> <span class="hljs-keyword">when</span> sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) >= <span class="hljs-number">0.5</span> <span class="hljs-keyword">then</span> <span class="hljs-number">1.0</span> <span class="hljs-keyword">else</span> <span class="hljs-number">0.0</span> <span class="hljs-keyword">end</span>)<span class="hljs-keyword">as</span> label
<span class="hljs-keyword">from</span>
- test_exploded t <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span>
- classification_model m <span class="hljs-keyword">ON</span> (t.feature = m.feature)
+ test_exploded t
+ <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> classification_model m
+ <span class="hljs-keyword">ON</span> (t.feature = m.feature)
<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
t.<span class="hljs-keyword">rowid</span>
),
submit <span class="hljs-keyword">as</span> (
<span class="hljs-keyword">select</span>
t.label <span class="hljs-keyword">as</span> actual,
- pd.label <span class="hljs-keyword">as</span> predicted,
- pd.prob <span class="hljs-keyword">as</span> probability
+ p.label <span class="hljs-keyword">as</span> predicted,
+ p.prob <span class="hljs-keyword">as</span> probability
<span class="hljs-keyword">from</span>
- a9a_test t <span class="hljs-keyword">JOIN</span> predict pd
- <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = pd.<span class="hljs-keyword">rowid</span>)
+ a9a_test t
+ <span class="hljs-keyword">JOIN</span> predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
)
-<span class="hljs-keyword">select</span> <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) / ${n_samples} <span class="hljs-keyword">from</span> submit
-<span class="hljs-keyword">where</span> actual = predicted;
+<span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ submit;
</code></pre>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">accuracy</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">0.8461396720103188</td>
+</tr>
+</tbody>
+</table>
<h1 id="comparison-with-the-other-binary-classifiers">Comparison with the other binary classifiers</h1>
<p>In the next part of this user guide, our binary classification tutorials introduce many different functions:</p>
<ul>
@@ -2405,15 +2455,15 @@ submit <span class="hljs-keyword">as</span> (
</ul>
<p>All of them actually have the same interface, but mathematical formulation and its implementation differ from each other.</p>
<p>In particular, the above sample queries are almost same as <a href="a9a_lr.html">a9a tutorial using Logistic Regression</a>. The difference is only in a choice of training function: <code>logress()</code> vs. <code>train_classifier()</code>.</p>
-<p>However, at the same time, the options <code>-loss logloss -opt SGD -reg no -eta simple -total_steps ${total_steps}</code> for <code>train_classifier</code> indicates that Hivemall uses the generic classifier as Logistic Regressor (<code>logress</code>). Hence, the accuracy of prediction based on either <code>logress</code> and <code>train_classifier</code> should be same under the configuration.</p>
+<p>However, at the same time, the options <code>-loss logloss -opt SGD -reg no</code> for <code>train_classifier</code> indicates that Hivemall uses the generic classifier as <code>logress</code>. Hence, the accuracy of prediction based on either <code>logress</code> and <code>train_classifier</code> would be (almost) same under the configuration.</p>
<p>In addition, <code>train_classifier</code> supports the <code>-mini_batch</code> option in a similar manner to <a href="a9a_minibatch.html">what <code>logress</code> does</a>. Thus, following two training queries show the same results:</p>
<pre><code class="lang-sql"><span class="hljs-keyword">select</span>
- logress(add_bias(features), label, <span class="hljs-string">'-total_steps ${total_steps} -mini_batch 10'</span>) <span class="hljs-keyword">as</span> (feature, weight)
+ logress(add_bias(features), label, <span class="hljs-string">'-mini_batch 10'</span>) <span class="hljs-keyword">as</span> (feature, weight)
<span class="hljs-keyword">from</span>
a9a_train
</code></pre>
<pre><code class="lang-sql"><span class="hljs-keyword">select</span>
- train_classifier(add_bias(features), label, <span class="hljs-string">'-loss logloss -opt SGD -reg no -eta simple -total_steps ${total_steps} -mini_batch 10'</span>) <span class="hljs-keyword">as</span> (feature, weight)
+ train_classifier(add_bias(features), label, <span class="hljs-string">'-loss logloss -opt SGD -reg no -mini_batch 10'</span>) <span class="hljs-keyword">as</span> (feature, weight)
<span class="hljs-keyword">from</span>
a9a_train
</code></pre>
@@ -2473,7 +2523,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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</div>
@@ -2503,7 +2553,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/kdd2010a.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/kdd2010a.html b/userguide/binaryclass/kdd2010a.html
index e8edf8e..c807a7c 100644
--- a/userguide/binaryclass/kdd2010a.html
+++ b/userguide/binaryclass/kdd2010a.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
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Random Forest
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<b>7.1.1.</b>
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[26/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/news20_generic.html
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+<!DOCTYPE HTML>
+<html lang="" >
+ <head>
+ <meta charset="UTF-8">
+ <meta content="text/html; charset=utf-8" http-equiv="Content-Type">
+ <title>General Binary Classifier · Hivemall User Manual</title>
+ <meta http-equiv="X-UA-Compatible" content="IE=edge" />
+ <meta name="description" content="">
+ <meta name="generator" content="GitBook 3.2.3">
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+ <link rel="next" href="news20_adagrad.html" />
+
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+ <link rel="prev" href="news20_scw.html" />
+
+
+ </head>
+ <body>
+
+<div class="book">
+ <div class="book-summary">
+
+
+<div id="book-search-input" role="search">
+ <input type="text" placeholder="Type to search" />
+</div>
+
+
+ <nav role="navigation">
+
+
+
+<ul class="summary">
+
+
+
+
+ <li>
+ <a href="https://hivemall.incubator.apache.org/" target="_blank" class="custom-link"><i class="fa fa-home"></i> Home</a>
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+
+
+
+ <li class="header">TABLE OF CONTENTS</li>
+
+
+
+ <li class="chapter " data-level="1.1" data-path="../">
+
+ <a href="../">
+
+
+ <b>1.1.</b>
+
+ Introduction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2" data-path="../getting_started/">
+
+ <a href="../getting_started/">
+
+
+ <b>1.2.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.2.1" data-path="../getting_started/installation.html">
+
+ <a href="../getting_started/installation.html">
+
+
+ <b>1.2.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.2" data-path="../getting_started/permanent-functions.html">
+
+ <a href="../getting_started/permanent-functions.html">
+
+
+ <b>1.2.2.</b>
+
+ Install as permanent functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.3" data-path="../getting_started/input-format.html">
+
+ <a href="../getting_started/input-format.html">
+
+
+ <b>1.2.3.</b>
+
+ Input Format
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.3" data-path="../misc/funcs.html">
+
+ <a href="../misc/funcs.html">
+
+
+ <b>1.3.</b>
+
+ List of Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4" data-path="../tips/">
+
+ <a href="../tips/">
+
+
+ <b>1.4.</b>
+
+ Tips for Effective Hivemall
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.4.1" data-path="../tips/addbias.html">
+
+ <a href="../tips/addbias.html">
+
+
+ <b>1.4.1.</b>
+
+ Explicit add_bias() for better prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.2" data-path="../tips/rand_amplify.html">
+
+ <a href="../tips/rand_amplify.html">
+
+
+ <b>1.4.2.</b>
+
+ Use rand_amplify() to better prediction results
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.3" data-path="../tips/rt_prediction.html">
+
+ <a href="../tips/rt_prediction.html">
+
+
+ <b>1.4.3.</b>
+
+ Real-time prediction on RDBMS
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.4" data-path="../tips/ensemble_learning.html">
+
+ <a href="../tips/ensemble_learning.html">
+
+
+ <b>1.4.4.</b>
+
+ Ensemble learning for stable prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.5" data-path="../tips/mixserver.html">
+
+ <a href="../tips/mixserver.html">
+
+
+ <b>1.4.5.</b>
+
+ Mixing models for a better prediction convergence (MIX server)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.6" data-path="../tips/emr.html">
+
+ <a href="../tips/emr.html">
+
+
+ <b>1.4.6.</b>
+
+ Run Hivemall on Amazon Elastic MapReduce
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.5" data-path="../tips/general_tips.html">
+
+ <a href="../tips/general_tips.html">
+
+
+ <b>1.5.</b>
+
+ General Hive/Hadoop Tips
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.5.1" data-path="../tips/rowid.html">
+
+ <a href="../tips/rowid.html">
+
+
+ <b>1.5.1.</b>
+
+ Adding rowid for each row
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.5.2" data-path="../tips/hadoop_tuning.html">
+
+ <a href="../tips/hadoop_tuning.html">
+
+
+ <b>1.5.2.</b>
+
+ Hadoop tuning for Hivemall
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.6" data-path="../troubleshooting/">
+
+ <a href="../troubleshooting/">
+
+
+ <b>1.6.</b>
+
+ Troubleshooting
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.6.1" data-path="../troubleshooting/oom.html">
+
+ <a href="../troubleshooting/oom.html">
+
+
+ <b>1.6.1.</b>
+
+ OutOfMemoryError in training
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.2" data-path="../troubleshooting/mapjoin_task_error.html">
+
+ <a href="../troubleshooting/mapjoin_task_error.html">
+
+
+ <b>1.6.2.</b>
+
+ SemanticException generate map join task error: Cannot serialize object
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.3" data-path="../troubleshooting/asterisk.html">
+
+ <a href="../troubleshooting/asterisk.html">
+
+
+ <b>1.6.3.</b>
+
+ Asterisk argument for UDTF does not work
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.4" data-path="../troubleshooting/num_mappers.html">
+
+ <a href="../troubleshooting/num_mappers.html">
+
+
+ <b>1.6.4.</b>
+
+ The number of mappers is less than input splits in Hadoop 2.x
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.5" data-path="../troubleshooting/mapjoin_classcastex.html">
+
+ <a href="../troubleshooting/mapjoin_classcastex.html">
+
+
+ <b>1.6.5.</b>
+
+ Map-side join causes ClassCastException on Tez
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part II - Generic Features</li>
+
+
+
+ <li class="chapter " data-level="2.1" data-path="../misc/generic_funcs.html">
+
+ <a href="../misc/generic_funcs.html">
+
+
+ <b>2.1.</b>
+
+ List of Generic Hivemall Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.2" data-path="../misc/topk.html">
+
+ <a href="../misc/topk.html">
+
+
+ <b>2.2.</b>
+
+ Efficient Top-K Query Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.3" data-path="../misc/tokenizer.html">
+
+ <a href="../misc/tokenizer.html">
+
+
+ <b>2.3.</b>
+
+ Text Tokenizer
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.4" data-path="../misc/approx.html">
+
+ <a href="../misc/approx.html">
+
+
+ <b>2.4.</b>
+
+ Approximate Aggregate Functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part III - Feature Engineering</li>
+
+
+
+ <li class="chapter " data-level="3.1" data-path="../ft_engineering/scaling.html">
+
+ <a href="../ft_engineering/scaling.html">
+
+
+ <b>3.1.</b>
+
+ Feature Scaling
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.2" data-path="../ft_engineering/hashing.html">
+
+ <a href="../ft_engineering/hashing.html">
+
+
+ <b>3.2.</b>
+
+ Feature Hashing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.3" data-path="../ft_engineering/selection.html">
+
+ <a href="../ft_engineering/selection.html">
+
+
+ <b>3.3.</b>
+
+ Feature Selection
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.4" data-path="../ft_engineering/binning.html">
+
+ <a href="../ft_engineering/binning.html">
+
+
+ <b>3.4.</b>
+
+ Feature Binning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.5" data-path="../ft_engineering/pairing.html">
+
+ <a href="../ft_engineering/pairing.html">
+
+
+ <b>3.5.</b>
+
+ Feature Paring
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.5.1" data-path="../ft_engineering/polynomial.html">
+
+ <a href="../ft_engineering/polynomial.html">
+
+
+ <b>3.5.1.</b>
+
+ Polynomial features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.6" data-path="../ft_engineering/ft_trans.html">
+
+ <a href="../ft_engineering/ft_trans.html">
+
+
+ <b>3.6.</b>
+
+ Feature Transformation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.6.1" data-path="../ft_engineering/vectorization.html">
+
+ <a href="../ft_engineering/vectorization.html">
+
+
+ <b>3.6.1.</b>
+
+ Feature vectorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.6.2" data-path="../ft_engineering/quantify.html">
+
+ <a href="../ft_engineering/quantify.html">
+
+
+ <b>3.6.2.</b>
+
+ Quantify non-number features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.7" data-path="../ft_engineering/term_vector.html">
+
+ <a href="../ft_engineering/term_vector.html">
+
+
+ <b>3.7.</b>
+
+ Term Vector Model
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.7.1" data-path="../ft_engineering/tfidf.html">
+
+ <a href="../ft_engineering/tfidf.html">
+
+
+ <b>3.7.1.</b>
+
+ TF-IDF Term Weighting
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.7.2" data-path="../ft_engineering/bm25.html">
+
+ <a href="../ft_engineering/bm25.html">
+
+
+ <b>3.7.2.</b>
+
+ Okapi BM25 Term Weighting
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IV - Evaluation</li>
+
+
+
+ <li class="chapter " data-level="4.1" data-path="../eval/binary_classification_measures.html">
+
+ <a href="../eval/binary_classification_measures.html">
+
+
+ <b>4.1.</b>
+
+ Binary Classification Metrics
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.1.1" data-path="../eval/auc.html">
+
+ <a href="../eval/auc.html">
+
+
+ <b>4.1.1.</b>
+
+ Area under the ROC curve
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="4.2" data-path="../eval/multilabel_classification_measures.html">
+
+ <a href="../eval/multilabel_classification_measures.html">
+
+
+ <b>4.2.</b>
+
+ Multi-label Classification Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.3" data-path="../eval/regression.html">
+
+ <a href="../eval/regression.html">
+
+
+ <b>4.3.</b>
+
+ Regression Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.4" data-path="../eval/rank.html">
+
+ <a href="../eval/rank.html">
+
+
+ <b>4.4.</b>
+
+ Ranking Measures
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.5" data-path="../eval/datagen.html">
+
+ <a href="../eval/datagen.html">
+
+
+ <b>4.5.</b>
+
+ Data Generation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.5.1" data-path="../eval/lr_datagen.html">
+
+ <a href="../eval/lr_datagen.html">
+
+
+ <b>4.5.1.</b>
+
+ Logistic Regression data generation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part V - Supervised Learning</li>
+
+
+
+ <li class="chapter " data-level="5.1" data-path="../supervised_learning/prediction.html">
+
+ <a href="../supervised_learning/prediction.html">
+
+
+ <b>5.1.</b>
+
+ How Prediction Works
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="5.2" data-path="../supervised_learning/tutorial.html">
+
+ <a href="../supervised_learning/tutorial.html">
+
+
+ <b>5.2.</b>
+
+ Step-by-Step Tutorial on Supervised Learning
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part VI - Binary Classification</li>
+
+
+
+ <li class="chapter " data-level="6.1" data-path="general.html">
+
+ <a href="general.html">
+
+
+ <b>6.1.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2" data-path="a9a.html">
+
+ <a href="a9a.html">
+
+
+ <b>6.2.</b>
+
+ a9a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.2.1" data-path="a9a_dataset.html">
+
+ <a href="a9a_dataset.html">
+
+
+ <b>6.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
+
+ <a href="a9a_generic.html">
+
+
+ <b>6.2.2.</b>
+
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
+ Logistic Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
+
+ <a href="a9a_minibatch.html">
+
+
+ <b>6.2.4.</b>
+
+ Mini-batch Gradient Descent
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.3" data-path="news20.html">
+
+ <a href="news20.html">
+
+
+ <b>6.3.</b>
+
+ News20 Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.3.1" data-path="news20_dataset.html">
+
+ <a href="news20_dataset.html">
+
+
+ <b>6.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.2" data-path="news20_pa.html">
+
+ <a href="news20_pa.html">
+
+
+ <b>6.3.2.</b>
+
+ Perceptron, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.3" data-path="news20_scw.html">
+
+ <a href="news20_scw.html">
+
+
+ <b>6.3.3.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter active" data-level="6.3.4" data-path="news20_generic.html">
+
+ <a href="news20_generic.html">
+
+
+ <b>6.3.4.</b>
+
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
+ AdaGradRDA, AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
+
+ <a href="news20_rf.html">
+
+
+ <b>6.3.6.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.4" data-path="kdd2010a.html">
+
+ <a href="kdd2010a.html">
+
+
+ <b>6.4.</b>
+
+ KDD2010a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.4.1" data-path="kdd2010a_dataset.html">
+
+ <a href="kdd2010a_dataset.html">
+
+
+ <b>6.4.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.4.2" data-path="kdd2010a_scw.html">
+
+ <a href="kdd2010a_scw.html">
+
+
+ <b>6.4.2.</b>
+
+ PA, CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.5" data-path="kdd2010b.html">
+
+ <a href="kdd2010b.html">
+
+
+ <b>6.5.</b>
+
+ KDD2010b Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.5.1" data-path="kdd2010b_dataset.html">
+
+ <a href="kdd2010b_dataset.html">
+
+
+ <b>6.5.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.5.2" data-path="kdd2010b_arow.html">
+
+ <a href="kdd2010b_arow.html">
+
+
+ <b>6.5.2.</b>
+
+ AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.6" data-path="webspam.html">
+
+ <a href="webspam.html">
+
+
+ <b>6.6.</b>
+
+ Webspam Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.6.1" data-path="webspam_dataset.html">
+
+ <a href="webspam_dataset.html">
+
+
+ <b>6.6.1.</b>
+
+ Data Pareparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.6.2" data-path="webspam_scw.html">
+
+ <a href="webspam_scw.html">
+
+
+ <b>6.6.2.</b>
+
+ PA1, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.7" data-path="titanic_rf.html">
+
+ <a href="titanic_rf.html">
+
+
+ <b>6.7.</b>
+
+ Kaggle Titanic Tutorial
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8" data-path="criteo.html">
+
+ <a href="criteo.html">
+
+
+ <b>6.8.</b>
+
+ Criteo Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.8.1" data-path="criteo_dataset.html">
+
+ <a href="criteo_dataset.html">
+
+
+ <b>6.8.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8.2" data-path="criteo_ffm.html">
+
+ <a href="criteo_ffm.html">
+
+
+ <b>6.8.2.</b>
+
+ Field-Aware Factorization Machines
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VII - Multiclass Classification</li>
+
+
+
+ <li class="chapter " data-level="7.1" data-path="../multiclass/news20.html">
+
+ <a href="../multiclass/news20.html">
+
+
+ <b>7.1.</b>
+
+ News20 Multiclass Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.1.1" data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>7.1.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.2" data-path="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+
+ <b>7.1.2.</b>
+
+ Data Preparation for one-vs-the-rest classifiers
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.3" data-path="../multiclass/news20_pa.html">
+
+ <a href="../multiclass/news20_pa.html">
+
+
+ <b>7.1.3.</b>
+
+ PA
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.4" data-path="../multiclass/news20_scw.html">
+
+ <a href="../multiclass/news20_scw.html">
+
+
+ <b>7.1.4.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.5" data-path="../multiclass/news20_ensemble.html">
+
+ <a href="../multiclass/news20_ensemble.html">
+
+
+ <b>7.1.5.</b>
+
+ Ensemble learning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.6" data-path="../multiclass/news20_one-vs-the-rest.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest.html">
+
+
+ <b>7.1.6.</b>
+
+ one-vs-the-rest Classifier
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="7.2" data-path="../multiclass/iris.html">
+
+ <a href="../multiclass/iris.html">
+
+
+ <b>7.2.</b>
+
+ Iris Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.2.1" data-path="../multiclass/iris_dataset.html">
+
+ <a href="../multiclass/iris_dataset.html">
+
+
+ <b>7.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.2" data-path="../multiclass/iris_scw.html">
+
+ <a href="../multiclass/iris_scw.html">
+
+
+ <b>7.2.2.</b>
+
+ SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.3" data-path="../multiclass/iris_randomforest.html">
+
+ <a href="../multiclass/iris_randomforest.html">
+
+
+ <b>7.2.3.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VIII - Regression</li>
+
+
+
+ <li class="chapter " data-level="8.1" data-path="../regression/general.html">
+
+ <a href="../regression/general.html">
+
+
+ <b>8.1.</b>
+
+ Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2" data-path="../regression/e2006.html">
+
+ <a href="../regression/e2006.html">
+
+
+ <b>8.2.</b>
+
+ E2006-tfidf Regression Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.2.1" data-path="../regression/e2006_dataset.html">
+
+ <a href="../regression/e2006_dataset.html">
+
+
+ <b>8.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
+
+ <a href="../regression/e2006_generic.html">
+
+
+ <b>8.2.2.</b>
+
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
+ Passive Aggressive, AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="8.3" data-path="../regression/kddcup12tr2.html">
+
+ <a href="../regression/kddcup12tr2.html">
+
+
+ <b>8.3.</b>
+
+ KDDCup 2012 Track 2 CTR Prediction Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.3.1" data-path="../regression/kddcup12tr2_dataset.html">
+
+ <a href="../regression/kddcup12tr2_dataset.html">
+
+
+ <b>8.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.2" data-path="../regression/kddcup12tr2_lr.html">
+
+ <a href="../regression/kddcup12tr2_lr.html">
+
+
+ <b>8.3.2.</b>
+
+ Logistic Regression, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.3" data-path="../regression/kddcup12tr2_lr_amplify.html">
+
+ <a href="../regression/kddcup12tr2_lr_amplify.html">
+
+
+ <b>8.3.3.</b>
+
+ Logistic Regression with amplifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.4" data-path="../regression/kddcup12tr2_adagrad.html">
+
+ <a href="../regression/kddcup12tr2_adagrad.html">
+
+
+ <b>8.3.4.</b>
+
+ AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IX - Recommendation</li>
+
+
+
+ <li class="chapter " data-level="9.1" data-path="../recommend/cf.html">
+
+ <a href="../recommend/cf.html">
+
+
+ <b>9.1.</b>
+
+ Collaborative Filtering
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.1.1" data-path="../recommend/item_based_cf.html">
+
+ <a href="../recommend/item_based_cf.html">
+
+
+ <b>9.1.1.</b>
+
+ Item-based Collaborative Filtering
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.2" data-path="../recommend/news20.html">
+
+ <a href="../recommend/news20.html">
+
+
+ <b>9.2.</b>
+
+ News20 Related Article Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.2.1" data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>9.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.2" data-path="../recommend/news20_jaccard.html">
+
+ <a href="../recommend/news20_jaccard.html">
+
+
+ <b>9.2.2.</b>
+
+ LSH/MinHash and Jaccard Similarity
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.3" data-path="../recommend/news20_knn.html">
+
+ <a href="../recommend/news20_knn.html">
+
+
+ <b>9.2.3.</b>
+
+ LSH/MinHash and Brute-force Search
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.4" data-path="../recommend/news20_bbit_minhash.html">
+
+ <a href="../recommend/news20_bbit_minhash.html">
+
+
+ <b>9.2.4.</b>
+
+ kNN search using b-Bits MinHash
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.3" data-path="../recommend/movielens.html">
+
+ <a href="../recommend/movielens.html">
+
+
+ <b>9.3.</b>
+
+ MovieLens Movie Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.3.1" data-path="../recommend/movielens_dataset.html">
+
+ <a href="../recommend/movielens_dataset.html">
+
+
+ <b>9.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.2" data-path="../recommend/movielens_cf.html">
+
+ <a href="../recommend/movielens_cf.html">
+
+
+ <b>9.3.2.</b>
+
+ Item-based Collaborative Filtering
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.3" data-path="../recommend/movielens_mf.html">
+
+ <a href="../recommend/movielens_mf.html">
+
+
+ <b>9.3.3.</b>
+
+ Matrix Factorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.4" data-path="../recommend/movielens_fm.html">
+
+ <a href="../recommend/movielens_fm.html">
+
+
+ <b>9.3.4.</b>
+
+ Factorization Machine
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.5" data-path="../recommend/movielens_slim.html">
+
+ <a href="../recommend/movielens_slim.html">
+
+
+ <b>9.3.5.</b>
+
+ SLIM for fast top-k Recommendation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.6" data-path="../recommend/movielens_cv.html">
+
+ <a href="../recommend/movielens_cv.html">
+
+
+ <b>9.3.6.</b>
+
+ 10-fold Cross Validation (Matrix Factorization)
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part X - Anomaly Detection</li>
+
+
+
+ <li class="chapter " data-level="10.1" data-path="../anomaly/lof.html">
+
+ <a href="../anomaly/lof.html">
+
+
+ <b>10.1.</b>
+
+ Outlier Detection using Local Outlier Factor (LOF)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.2" data-path="../anomaly/sst.html">
+
+ <a href="../anomaly/sst.html">
+
+
+ <b>10.2.</b>
+
+ Change-Point Detection using Singular Spectrum Transformation (SST)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.3" data-path="../anomaly/changefinder.html">
+
+ <a href="../anomaly/changefinder.html">
+
+
+ <b>10.3.</b>
+
+ ChangeFinder: Detecting Outlier and Change-Point Simultaneously
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XI - Clustering</li>
+
+
+
+ <li class="chapter " data-level="11.1" data-path="../clustering/lda.html">
+
+ <a href="../clustering/lda.html">
+
+
+ <b>11.1.</b>
+
+ Latent Dirichlet Allocation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="11.2" data-path="../clustering/plsa.html">
+
+ <a href="../clustering/plsa.html">
+
+
+ <b>11.2.</b>
+
+ Probabilistic Latent Semantic Analysis
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XII - GeoSpatial Functions</li>
+
+
+
+ <li class="chapter " data-level="12.1" data-path="../geospatial/latlon.html">
+
+ <a href="../geospatial/latlon.html">
+
+
+ <b>12.1.</b>
+
+ Lat/Lon functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIII - Hivemall on Spark</li>
+
+
+
+ <li class="chapter " data-level="13.1" data-path="../spark/getting_started/">
+
+ <a href="../spark/getting_started/">
+
+
+ <b>13.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.1.1" data-path="../spark/getting_started/installation.html">
+
+ <a href="../spark/getting_started/installation.html">
+
+
+ <b>13.1.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.2" data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.2.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.2.1" data-path="../spark/binaryclass/a9a_df.html">
+
+ <a href="../spark/binaryclass/a9a_df.html">
+
+
+ <b>13.2.1.</b>
+
+ a9a Tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.2.2" data-path="../spark/binaryclass/a9a_sql.html">
+
+ <a href="../spark/binaryclass/a9a_sql.html">
+
+
+ <b>13.2.2.</b>
+
+ a9a Tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.3" data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.3.</b>
+
+ Regression
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.3.1" data-path="../spark/regression/e2006_df.html">
+
+ <a href="../spark/regression/e2006_df.html">
+
+
+ <b>13.3.1.</b>
+
+ E2006-tfidf Regression Tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.3.2" data-path="../spark/regression/e2006_sql.html">
+
+ <a href="../spark/regression/e2006_sql.html">
+
+
+ <b>13.3.2.</b>
+
+ E2006-tfidf Regression Tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.4" data-path="../spark/misc/misc.html">
+
+ <a href="../spark/misc/misc.html">
+
+
+ <b>13.4.</b>
+
+ Generic Features
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.4.1" data-path="../spark/misc/topk_join.html">
+
+ <a href="../spark/misc/topk_join.html">
+
+
+ <b>13.4.1.</b>
+
+ Top-k Join Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.4.2" data-path="../spark/misc/functions.html">
+
+ <a href="../spark/misc/functions.html">
+
+
+ <b>13.4.2.</b>
+
+ Other Utility Functions
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - Hivemall on Docker</li>
+
+
+
+ <li class="chapter " data-level="14.1" data-path="../docker/getting_started.html">
+
+ <a href="../docker/getting_started.html">
+
+
+ <b>14.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - External References</li>
+
+
+
+ <li class="chapter " data-level="15.1" >
+
+ <a target="_blank" href="https://github.com/daijyc/hivemall/wiki/PigHome">
+
+
+ <b>15.1.</b>
+
+ Hivemall on Apache Pig
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+ <li>
+ <a href="https://www.gitbook.com" target="blank" class="gitbook-link">
+ Published with GitBook
+ </a>
+ </li>
+</ul>
+
+
+ </nav>
+
+
+ </div>
+
+ <div class="book-body">
+
+ <div class="body-inner">
+
+
+
+<div class="book-header" role="navigation">
+
+
+ <!-- Title -->
+ <h1>
+ <i class="fa fa-circle-o-notch fa-spin"></i>
+ <a href=".." >General Binary Classifier</a>
+ </h1>
+</div>
+
+
+
+
+ <div class="page-wrapper" tabindex="-1" role="main">
+ <div class="page-inner">
+
+<div id="book-search-results">
+ <div class="search-noresults">
+
+ <section class="normal markdown-section">
+
+ <!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<p>In this tutorial, we build a binary classification model using general classifier.</p>
+<!-- toc --><div id="toc" class="toc">
+
+<ul>
+<li><a href="#training">Training</a></li>
+<li><a href="#prediction">prediction</a></li>
+<li><a href="#evaluation">evaluation</a></li>
+</ul>
+
+</div><!-- tocstop -->
+<h2 id="training">Training</h2>
+<pre><code class="lang-sql"><span class="hljs-comment">-- set mapred.reduce.tasks=3; -- explicitly use 3 reducers</span>
+
+<span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_generic_model;
+<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> news20b_generic_model <span class="hljs-keyword">as</span>
+<span class="hljs-keyword">select</span>
+ feature,
+ voted_avg(weight) <span class="hljs-keyword">as</span> weight
+<span class="hljs-keyword">from</span>
+ (<span class="hljs-keyword">select</span>
+ train_classifier(
+ add_bias(features), label,
+ <span class="hljs-string">'-loss logistic -opt AdamHD -reg l1 -iters 20'</span>
+ ) <span class="hljs-keyword">as</span> (feature,weight)
+ <span class="hljs-keyword">from</span>
+ news20b_train_x3
+ ) t
+<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature;
+</code></pre>
+<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>Default (Adagrad+RDA), AdaDelta, Adam, and AdamHD is worth trying in my experience.</p></div></div>
+<h2 id="prediction">prediction</h2>
+<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> news20b_generic_predict
+<span class="hljs-keyword">as</span>
+<span class="hljs-keyword">select</span>
+ t.<span class="hljs-keyword">rowid</span>,
+ <span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>) <span class="hljs-keyword">as</span> total_weight,
+ <span class="hljs-keyword">case</span> <span class="hljs-keyword">when</span> <span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>) > <span class="hljs-number">0.0</span> <span class="hljs-keyword">then</span> <span class="hljs-number">1</span> <span class="hljs-keyword">else</span> <span class="hljs-number">-1</span> <span class="hljs-keyword">end</span> <span class="hljs-keyword">as</span> label
+<span class="hljs-keyword">from</span>
+ news20b_test_exploded t <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span>
+ news20b_generic_model m <span class="hljs-keyword">ON</span> (t.feature = m.feature)
+<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
+ t.<span class="hljs-keyword">rowid</span>;
+</code></pre>
+<h2 id="evaluation">evaluation</h2>
+<pre><code class="lang-sql">WITH submit as (
+<span class="hljs-keyword">select</span>
+ t.label <span class="hljs-keyword">as</span> actual,
+ p.label <span class="hljs-keyword">as</span> predicted
+<span class="hljs-keyword">from</span>
+ news20b_test t
+ <span class="hljs-keyword">JOIN</span> news20b_generic_predict p
+ <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>)
+)
+<span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual = predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ submit;
+</code></pre>
+<blockquote>
+<p>0.967173738991193 (<code>-opt AdamHD -reg l1</code>)
+<div id="page-footer" class="localized-footer"><hr><!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<p><sub><font color="gray">
+Apache Hivemall is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator.
+</font></sub></p>
+</div></p>
+</blockquote>
+
+
+ </section>
+
+ </div>
+ <div class="search-results">
+ <div class="has-results">
+
+ <h1 class="search-results-title"><span class='search-results-count'></span> results matching "<span class='search-query'></span>"</h1>
+ <ul class="search-results-list"></ul>
+
+ </div>
+ <div class="no-results">
+
+ <h1 class="search-results-title">No results matching "<span class='search-query'></span>"</h1>
+
+ </div>
+ </div>
+</div>
+
+ </div>
+ </div>
+
+ </div>
+
+
+
+
+ </div>
+
+ <script>
+ var gitbook = gitbook || [];
+ gitbook.push(function() {
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+ </body>
+</html>
+
[08/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/search_index.json
----------------------------------------------------------------------
diff --git a/userguide/search_index.json b/userguide/search_index.json
index dc97c49..6bb32ab 100644
--- a/userguide/search_index.json
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<TRUNCATED>
[31/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/a9a_generic.html
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+
+<!DOCTYPE HTML>
+<html lang="" >
+ <head>
+ <meta charset="UTF-8">
+ <meta content="text/html; charset=utf-8" http-equiv="Content-Type">
+ <title>General Binary Classifier · Hivemall User Manual</title>
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+ <link rel="next" href="a9a_lr.html" />
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+ <link rel="prev" href="a9a_dataset.html" />
+
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+ </head>
+ <body>
+
+<div class="book">
+ <div class="book-summary">
+
+
+<div id="book-search-input" role="search">
+ <input type="text" placeholder="Type to search" />
+</div>
+
+
+ <nav role="navigation">
+
+
+
+<ul class="summary">
+
+
+
+
+ <li>
+ <a href="https://hivemall.incubator.apache.org/" target="_blank" class="custom-link"><i class="fa fa-home"></i> Home</a>
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+
+
+
+ <li class="header">TABLE OF CONTENTS</li>
+
+
+
+ <li class="chapter " data-level="1.1" data-path="../">
+
+ <a href="../">
+
+
+ <b>1.1.</b>
+
+ Introduction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2" data-path="../getting_started/">
+
+ <a href="../getting_started/">
+
+
+ <b>1.2.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.2.1" data-path="../getting_started/installation.html">
+
+ <a href="../getting_started/installation.html">
+
+
+ <b>1.2.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.2" data-path="../getting_started/permanent-functions.html">
+
+ <a href="../getting_started/permanent-functions.html">
+
+
+ <b>1.2.2.</b>
+
+ Install as permanent functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.3" data-path="../getting_started/input-format.html">
+
+ <a href="../getting_started/input-format.html">
+
+
+ <b>1.2.3.</b>
+
+ Input Format
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.3" data-path="../misc/funcs.html">
+
+ <a href="../misc/funcs.html">
+
+
+ <b>1.3.</b>
+
+ List of Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4" data-path="../tips/">
+
+ <a href="../tips/">
+
+
+ <b>1.4.</b>
+
+ Tips for Effective Hivemall
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.4.1" data-path="../tips/addbias.html">
+
+ <a href="../tips/addbias.html">
+
+
+ <b>1.4.1.</b>
+
+ Explicit add_bias() for better prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.2" data-path="../tips/rand_amplify.html">
+
+ <a href="../tips/rand_amplify.html">
+
+
+ <b>1.4.2.</b>
+
+ Use rand_amplify() to better prediction results
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.3" data-path="../tips/rt_prediction.html">
+
+ <a href="../tips/rt_prediction.html">
+
+
+ <b>1.4.3.</b>
+
+ Real-time prediction on RDBMS
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.4" data-path="../tips/ensemble_learning.html">
+
+ <a href="../tips/ensemble_learning.html">
+
+
+ <b>1.4.4.</b>
+
+ Ensemble learning for stable prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.5" data-path="../tips/mixserver.html">
+
+ <a href="../tips/mixserver.html">
+
+
+ <b>1.4.5.</b>
+
+ Mixing models for a better prediction convergence (MIX server)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.6" data-path="../tips/emr.html">
+
+ <a href="../tips/emr.html">
+
+
+ <b>1.4.6.</b>
+
+ Run Hivemall on Amazon Elastic MapReduce
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.5" data-path="../tips/general_tips.html">
+
+ <a href="../tips/general_tips.html">
+
+
+ <b>1.5.</b>
+
+ General Hive/Hadoop Tips
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.5.1" data-path="../tips/rowid.html">
+
+ <a href="../tips/rowid.html">
+
+
+ <b>1.5.1.</b>
+
+ Adding rowid for each row
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.5.2" data-path="../tips/hadoop_tuning.html">
+
+ <a href="../tips/hadoop_tuning.html">
+
+
+ <b>1.5.2.</b>
+
+ Hadoop tuning for Hivemall
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.6" data-path="../troubleshooting/">
+
+ <a href="../troubleshooting/">
+
+
+ <b>1.6.</b>
+
+ Troubleshooting
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.6.1" data-path="../troubleshooting/oom.html">
+
+ <a href="../troubleshooting/oom.html">
+
+
+ <b>1.6.1.</b>
+
+ OutOfMemoryError in training
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.2" data-path="../troubleshooting/mapjoin_task_error.html">
+
+ <a href="../troubleshooting/mapjoin_task_error.html">
+
+
+ <b>1.6.2.</b>
+
+ SemanticException generate map join task error: Cannot serialize object
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.3" data-path="../troubleshooting/asterisk.html">
+
+ <a href="../troubleshooting/asterisk.html">
+
+
+ <b>1.6.3.</b>
+
+ Asterisk argument for UDTF does not work
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.4" data-path="../troubleshooting/num_mappers.html">
+
+ <a href="../troubleshooting/num_mappers.html">
+
+
+ <b>1.6.4.</b>
+
+ The number of mappers is less than input splits in Hadoop 2.x
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.5" data-path="../troubleshooting/mapjoin_classcastex.html">
+
+ <a href="../troubleshooting/mapjoin_classcastex.html">
+
+
+ <b>1.6.5.</b>
+
+ Map-side join causes ClassCastException on Tez
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part II - Generic Features</li>
+
+
+
+ <li class="chapter " data-level="2.1" data-path="../misc/generic_funcs.html">
+
+ <a href="../misc/generic_funcs.html">
+
+
+ <b>2.1.</b>
+
+ List of Generic Hivemall Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.2" data-path="../misc/topk.html">
+
+ <a href="../misc/topk.html">
+
+
+ <b>2.2.</b>
+
+ Efficient Top-K Query Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.3" data-path="../misc/tokenizer.html">
+
+ <a href="../misc/tokenizer.html">
+
+
+ <b>2.3.</b>
+
+ Text Tokenizer
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.4" data-path="../misc/approx.html">
+
+ <a href="../misc/approx.html">
+
+
+ <b>2.4.</b>
+
+ Approximate Aggregate Functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part III - Feature Engineering</li>
+
+
+
+ <li class="chapter " data-level="3.1" data-path="../ft_engineering/scaling.html">
+
+ <a href="../ft_engineering/scaling.html">
+
+
+ <b>3.1.</b>
+
+ Feature Scaling
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.2" data-path="../ft_engineering/hashing.html">
+
+ <a href="../ft_engineering/hashing.html">
+
+
+ <b>3.2.</b>
+
+ Feature Hashing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.3" data-path="../ft_engineering/selection.html">
+
+ <a href="../ft_engineering/selection.html">
+
+
+ <b>3.3.</b>
+
+ Feature Selection
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.4" data-path="../ft_engineering/binning.html">
+
+ <a href="../ft_engineering/binning.html">
+
+
+ <b>3.4.</b>
+
+ Feature Binning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.5" data-path="../ft_engineering/pairing.html">
+
+ <a href="../ft_engineering/pairing.html">
+
+
+ <b>3.5.</b>
+
+ Feature Paring
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.5.1" data-path="../ft_engineering/polynomial.html">
+
+ <a href="../ft_engineering/polynomial.html">
+
+
+ <b>3.5.1.</b>
+
+ Polynomial features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.6" data-path="../ft_engineering/ft_trans.html">
+
+ <a href="../ft_engineering/ft_trans.html">
+
+
+ <b>3.6.</b>
+
+ Feature Transformation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.6.1" data-path="../ft_engineering/vectorization.html">
+
+ <a href="../ft_engineering/vectorization.html">
+
+
+ <b>3.6.1.</b>
+
+ Feature vectorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.6.2" data-path="../ft_engineering/quantify.html">
+
+ <a href="../ft_engineering/quantify.html">
+
+
+ <b>3.6.2.</b>
+
+ Quantify non-number features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.7" data-path="../ft_engineering/term_vector.html">
+
+ <a href="../ft_engineering/term_vector.html">
+
+
+ <b>3.7.</b>
+
+ Term Vector Model
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.7.1" data-path="../ft_engineering/tfidf.html">
+
+ <a href="../ft_engineering/tfidf.html">
+
+
+ <b>3.7.1.</b>
+
+ TF-IDF Term Weighting
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.7.2" data-path="../ft_engineering/bm25.html">
+
+ <a href="../ft_engineering/bm25.html">
+
+
+ <b>3.7.2.</b>
+
+ Okapi BM25 Term Weighting
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IV - Evaluation</li>
+
+
+
+ <li class="chapter " data-level="4.1" data-path="../eval/binary_classification_measures.html">
+
+ <a href="../eval/binary_classification_measures.html">
+
+
+ <b>4.1.</b>
+
+ Binary Classification Metrics
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.1.1" data-path="../eval/auc.html">
+
+ <a href="../eval/auc.html">
+
+
+ <b>4.1.1.</b>
+
+ Area under the ROC curve
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="4.2" data-path="../eval/multilabel_classification_measures.html">
+
+ <a href="../eval/multilabel_classification_measures.html">
+
+
+ <b>4.2.</b>
+
+ Multi-label Classification Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.3" data-path="../eval/regression.html">
+
+ <a href="../eval/regression.html">
+
+
+ <b>4.3.</b>
+
+ Regression Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.4" data-path="../eval/rank.html">
+
+ <a href="../eval/rank.html">
+
+
+ <b>4.4.</b>
+
+ Ranking Measures
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.5" data-path="../eval/datagen.html">
+
+ <a href="../eval/datagen.html">
+
+
+ <b>4.5.</b>
+
+ Data Generation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.5.1" data-path="../eval/lr_datagen.html">
+
+ <a href="../eval/lr_datagen.html">
+
+
+ <b>4.5.1.</b>
+
+ Logistic Regression data generation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part V - Supervised Learning</li>
+
+
+
+ <li class="chapter " data-level="5.1" data-path="../supervised_learning/prediction.html">
+
+ <a href="../supervised_learning/prediction.html">
+
+
+ <b>5.1.</b>
+
+ How Prediction Works
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="5.2" data-path="../supervised_learning/tutorial.html">
+
+ <a href="../supervised_learning/tutorial.html">
+
+
+ <b>5.2.</b>
+
+ Step-by-Step Tutorial on Supervised Learning
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part VI - Binary Classification</li>
+
+
+
+ <li class="chapter " data-level="6.1" data-path="general.html">
+
+ <a href="general.html">
+
+
+ <b>6.1.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2" data-path="a9a.html">
+
+ <a href="a9a.html">
+
+
+ <b>6.2.</b>
+
+ a9a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.2.1" data-path="a9a_dataset.html">
+
+ <a href="a9a_dataset.html">
+
+
+ <b>6.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter active" data-level="6.2.2" data-path="a9a_generic.html">
+
+ <a href="a9a_generic.html">
+
+
+ <b>6.2.2.</b>
+
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
+ Logistic Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
+
+ <a href="a9a_minibatch.html">
+
+
+ <b>6.2.4.</b>
+
+ Mini-batch Gradient Descent
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.3" data-path="news20.html">
+
+ <a href="news20.html">
+
+
+ <b>6.3.</b>
+
+ News20 Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.3.1" data-path="news20_dataset.html">
+
+ <a href="news20_dataset.html">
+
+
+ <b>6.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.2" data-path="news20_pa.html">
+
+ <a href="news20_pa.html">
+
+
+ <b>6.3.2.</b>
+
+ Perceptron, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.3" data-path="news20_scw.html">
+
+ <a href="news20_scw.html">
+
+
+ <b>6.3.3.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
+
+ <a href="news20_generic.html">
+
+
+ <b>6.3.4.</b>
+
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
+ AdaGradRDA, AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
+
+ <a href="news20_rf.html">
+
+
+ <b>6.3.6.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.4" data-path="kdd2010a.html">
+
+ <a href="kdd2010a.html">
+
+
+ <b>6.4.</b>
+
+ KDD2010a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.4.1" data-path="kdd2010a_dataset.html">
+
+ <a href="kdd2010a_dataset.html">
+
+
+ <b>6.4.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.4.2" data-path="kdd2010a_scw.html">
+
+ <a href="kdd2010a_scw.html">
+
+
+ <b>6.4.2.</b>
+
+ PA, CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.5" data-path="kdd2010b.html">
+
+ <a href="kdd2010b.html">
+
+
+ <b>6.5.</b>
+
+ KDD2010b Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.5.1" data-path="kdd2010b_dataset.html">
+
+ <a href="kdd2010b_dataset.html">
+
+
+ <b>6.5.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.5.2" data-path="kdd2010b_arow.html">
+
+ <a href="kdd2010b_arow.html">
+
+
+ <b>6.5.2.</b>
+
+ AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.6" data-path="webspam.html">
+
+ <a href="webspam.html">
+
+
+ <b>6.6.</b>
+
+ Webspam Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.6.1" data-path="webspam_dataset.html">
+
+ <a href="webspam_dataset.html">
+
+
+ <b>6.6.1.</b>
+
+ Data Pareparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.6.2" data-path="webspam_scw.html">
+
+ <a href="webspam_scw.html">
+
+
+ <b>6.6.2.</b>
+
+ PA1, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.7" data-path="titanic_rf.html">
+
+ <a href="titanic_rf.html">
+
+
+ <b>6.7.</b>
+
+ Kaggle Titanic Tutorial
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8" data-path="criteo.html">
+
+ <a href="criteo.html">
+
+
+ <b>6.8.</b>
+
+ Criteo Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.8.1" data-path="criteo_dataset.html">
+
+ <a href="criteo_dataset.html">
+
+
+ <b>6.8.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8.2" data-path="criteo_ffm.html">
+
+ <a href="criteo_ffm.html">
+
+
+ <b>6.8.2.</b>
+
+ Field-Aware Factorization Machines
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VII - Multiclass Classification</li>
+
+
+
+ <li class="chapter " data-level="7.1" data-path="../multiclass/news20.html">
+
+ <a href="../multiclass/news20.html">
+
+
+ <b>7.1.</b>
+
+ News20 Multiclass Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.1.1" data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>7.1.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.2" data-path="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+
+ <b>7.1.2.</b>
+
+ Data Preparation for one-vs-the-rest classifiers
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.3" data-path="../multiclass/news20_pa.html">
+
+ <a href="../multiclass/news20_pa.html">
+
+
+ <b>7.1.3.</b>
+
+ PA
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.4" data-path="../multiclass/news20_scw.html">
+
+ <a href="../multiclass/news20_scw.html">
+
+
+ <b>7.1.4.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.5" data-path="../multiclass/news20_ensemble.html">
+
+ <a href="../multiclass/news20_ensemble.html">
+
+
+ <b>7.1.5.</b>
+
+ Ensemble learning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.6" data-path="../multiclass/news20_one-vs-the-rest.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest.html">
+
+
+ <b>7.1.6.</b>
+
+ one-vs-the-rest Classifier
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="7.2" data-path="../multiclass/iris.html">
+
+ <a href="../multiclass/iris.html">
+
+
+ <b>7.2.</b>
+
+ Iris Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.2.1" data-path="../multiclass/iris_dataset.html">
+
+ <a href="../multiclass/iris_dataset.html">
+
+
+ <b>7.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.2" data-path="../multiclass/iris_scw.html">
+
+ <a href="../multiclass/iris_scw.html">
+
+
+ <b>7.2.2.</b>
+
+ SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.3" data-path="../multiclass/iris_randomforest.html">
+
+ <a href="../multiclass/iris_randomforest.html">
+
+
+ <b>7.2.3.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VIII - Regression</li>
+
+
+
+ <li class="chapter " data-level="8.1" data-path="../regression/general.html">
+
+ <a href="../regression/general.html">
+
+
+ <b>8.1.</b>
+
+ Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2" data-path="../regression/e2006.html">
+
+ <a href="../regression/e2006.html">
+
+
+ <b>8.2.</b>
+
+ E2006-tfidf Regression Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.2.1" data-path="../regression/e2006_dataset.html">
+
+ <a href="../regression/e2006_dataset.html">
+
+
+ <b>8.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
+
+ <a href="../regression/e2006_generic.html">
+
+
+ <b>8.2.2.</b>
+
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
+ Passive Aggressive, AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="8.3" data-path="../regression/kddcup12tr2.html">
+
+ <a href="../regression/kddcup12tr2.html">
+
+
+ <b>8.3.</b>
+
+ KDDCup 2012 Track 2 CTR Prediction Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.3.1" data-path="../regression/kddcup12tr2_dataset.html">
+
+ <a href="../regression/kddcup12tr2_dataset.html">
+
+
+ <b>8.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.2" data-path="../regression/kddcup12tr2_lr.html">
+
+ <a href="../regression/kddcup12tr2_lr.html">
+
+
+ <b>8.3.2.</b>
+
+ Logistic Regression, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.3" data-path="../regression/kddcup12tr2_lr_amplify.html">
+
+ <a href="../regression/kddcup12tr2_lr_amplify.html">
+
+
+ <b>8.3.3.</b>
+
+ Logistic Regression with amplifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.4" data-path="../regression/kddcup12tr2_adagrad.html">
+
+ <a href="../regression/kddcup12tr2_adagrad.html">
+
+
+ <b>8.3.4.</b>
+
+ AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IX - Recommendation</li>
+
+
+
+ <li class="chapter " data-level="9.1" data-path="../recommend/cf.html">
+
+ <a href="../recommend/cf.html">
+
+
+ <b>9.1.</b>
+
+ Collaborative Filtering
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.1.1" data-path="../recommend/item_based_cf.html">
+
+ <a href="../recommend/item_based_cf.html">
+
+
+ <b>9.1.1.</b>
+
+ Item-based Collaborative Filtering
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.2" data-path="../recommend/news20.html">
+
+ <a href="../recommend/news20.html">
+
+
+ <b>9.2.</b>
+
+ News20 Related Article Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.2.1" data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>9.2.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.2" data-path="../recommend/news20_jaccard.html">
+
+ <a href="../recommend/news20_jaccard.html">
+
+
+ <b>9.2.2.</b>
+
+ LSH/MinHash and Jaccard Similarity
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.3" data-path="../recommend/news20_knn.html">
+
+ <a href="../recommend/news20_knn.html">
+
+
+ <b>9.2.3.</b>
+
+ LSH/MinHash and Brute-force Search
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.4" data-path="../recommend/news20_bbit_minhash.html">
+
+ <a href="../recommend/news20_bbit_minhash.html">
+
+
+ <b>9.2.4.</b>
+
+ kNN search using b-Bits MinHash
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.3" data-path="../recommend/movielens.html">
+
+ <a href="../recommend/movielens.html">
+
+
+ <b>9.3.</b>
+
+ MovieLens Movie Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.3.1" data-path="../recommend/movielens_dataset.html">
+
+ <a href="../recommend/movielens_dataset.html">
+
+
+ <b>9.3.1.</b>
+
+ Data Preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.2" data-path="../recommend/movielens_cf.html">
+
+ <a href="../recommend/movielens_cf.html">
+
+
+ <b>9.3.2.</b>
+
+ Item-based Collaborative Filtering
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.3" data-path="../recommend/movielens_mf.html">
+
+ <a href="../recommend/movielens_mf.html">
+
+
+ <b>9.3.3.</b>
+
+ Matrix Factorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.4" data-path="../recommend/movielens_fm.html">
+
+ <a href="../recommend/movielens_fm.html">
+
+
+ <b>9.3.4.</b>
+
+ Factorization Machine
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.5" data-path="../recommend/movielens_slim.html">
+
+ <a href="../recommend/movielens_slim.html">
+
+
+ <b>9.3.5.</b>
+
+ SLIM for fast top-k Recommendation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.6" data-path="../recommend/movielens_cv.html">
+
+ <a href="../recommend/movielens_cv.html">
+
+
+ <b>9.3.6.</b>
+
+ 10-fold Cross Validation (Matrix Factorization)
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part X - Anomaly Detection</li>
+
+
+
+ <li class="chapter " data-level="10.1" data-path="../anomaly/lof.html">
+
+ <a href="../anomaly/lof.html">
+
+
+ <b>10.1.</b>
+
+ Outlier Detection using Local Outlier Factor (LOF)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.2" data-path="../anomaly/sst.html">
+
+ <a href="../anomaly/sst.html">
+
+
+ <b>10.2.</b>
+
+ Change-Point Detection using Singular Spectrum Transformation (SST)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.3" data-path="../anomaly/changefinder.html">
+
+ <a href="../anomaly/changefinder.html">
+
+
+ <b>10.3.</b>
+
+ ChangeFinder: Detecting Outlier and Change-Point Simultaneously
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XI - Clustering</li>
+
+
+
+ <li class="chapter " data-level="11.1" data-path="../clustering/lda.html">
+
+ <a href="../clustering/lda.html">
+
+
+ <b>11.1.</b>
+
+ Latent Dirichlet Allocation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="11.2" data-path="../clustering/plsa.html">
+
+ <a href="../clustering/plsa.html">
+
+
+ <b>11.2.</b>
+
+ Probabilistic Latent Semantic Analysis
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XII - GeoSpatial Functions</li>
+
+
+
+ <li class="chapter " data-level="12.1" data-path="../geospatial/latlon.html">
+
+ <a href="../geospatial/latlon.html">
+
+
+ <b>12.1.</b>
+
+ Lat/Lon functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIII - Hivemall on Spark</li>
+
+
+
+ <li class="chapter " data-level="13.1" data-path="../spark/getting_started/">
+
+ <a href="../spark/getting_started/">
+
+
+ <b>13.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.1.1" data-path="../spark/getting_started/installation.html">
+
+ <a href="../spark/getting_started/installation.html">
+
+
+ <b>13.1.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.2" data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.2.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.2.1" data-path="../spark/binaryclass/a9a_df.html">
+
+ <a href="../spark/binaryclass/a9a_df.html">
+
+
+ <b>13.2.1.</b>
+
+ a9a Tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.2.2" data-path="../spark/binaryclass/a9a_sql.html">
+
+ <a href="../spark/binaryclass/a9a_sql.html">
+
+
+ <b>13.2.2.</b>
+
+ a9a Tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.3" data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.3.</b>
+
+ Regression
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.3.1" data-path="../spark/regression/e2006_df.html">
+
+ <a href="../spark/regression/e2006_df.html">
+
+
+ <b>13.3.1.</b>
+
+ E2006-tfidf Regression Tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.3.2" data-path="../spark/regression/e2006_sql.html">
+
+ <a href="../spark/regression/e2006_sql.html">
+
+
+ <b>13.3.2.</b>
+
+ E2006-tfidf Regression Tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.4" data-path="../spark/misc/misc.html">
+
+ <a href="../spark/misc/misc.html">
+
+
+ <b>13.4.</b>
+
+ Generic Features
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.4.1" data-path="../spark/misc/topk_join.html">
+
+ <a href="../spark/misc/topk_join.html">
+
+
+ <b>13.4.1.</b>
+
+ Top-k Join Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.4.2" data-path="../spark/misc/functions.html">
+
+ <a href="../spark/misc/functions.html">
+
+
+ <b>13.4.2.</b>
+
+ Other Utility Functions
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - Hivemall on Docker</li>
+
+
+
+ <li class="chapter " data-level="14.1" data-path="../docker/getting_started.html">
+
+ <a href="../docker/getting_started.html">
+
+
+ <b>14.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - External References</li>
+
+
+
+ <li class="chapter " data-level="15.1" >
+
+ <a target="_blank" href="https://github.com/daijyc/hivemall/wiki/PigHome">
+
+
+ <b>15.1.</b>
+
+ Hivemall on Apache Pig
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+ <li>
+ <a href="https://www.gitbook.com" target="blank" class="gitbook-link">
+ Published with GitBook
+ </a>
+ </li>
+</ul>
+
+
+ </nav>
+
+
+ </div>
+
+ <div class="book-body">
+
+ <div class="body-inner">
+
+
+
+<div class="book-header" role="navigation">
+
+
+ <!-- Title -->
+ <h1>
+ <i class="fa fa-circle-o-notch fa-spin"></i>
+ <a href=".." >General Binary Classifier</a>
+ </h1>
+</div>
+
+
+
+
+ <div class="page-wrapper" tabindex="-1" role="main">
+ <div class="page-inner">
+
+<div id="book-search-results">
+ <div class="search-noresults">
+
+ <section class="normal markdown-section">
+
+ <!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<p>This page shows the usage of General Binary Classifier using a9a dataset.</p>
+<!-- toc --><div id="toc" class="toc">
+
+<ul>
+<li><a href="#training">Training</a></li>
+<li><a href="#prediction">Prediction</a></li>
+<li><a href="#evaluation">Evaluation</a></li>
+</ul>
+
+</div><!-- tocstop -->
+<h1 id="training">Training</h1>
+<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> <span class="hljs-keyword">model</span>
+<span class="hljs-keyword">as</span>
+<span class="hljs-keyword">select</span>
+ feature,
+ <span class="hljs-keyword">avg</span>(weight) <span class="hljs-keyword">as</span> weight
+<span class="hljs-keyword">from</span> (
+ <span class="hljs-keyword">select</span>
+ train_classifier(
+ add_bias(features), label,
+ <span class="hljs-string">"-loss logistic -iter 30"</span>
+ ) <span class="hljs-keyword">as</span> (feature,weight)
+ <span class="hljs-keyword">from</span>
+ a9a_train
+ ) t
+<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span> feature;
+</code></pre>
+<h1 id="prediction">Prediction</h1>
+<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> predict
+<span class="hljs-keyword">as</span>
+<span class="hljs-keyword">WITH</span> exploded <span class="hljs-keyword">as</span> (
+<span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">rowid</span>,
+ label,
+ extract_feature(feature) <span class="hljs-keyword">as</span> feature,
+ extract_weight(feature) <span class="hljs-keyword">as</span> <span class="hljs-keyword">value</span>
+<span class="hljs-keyword">from</span>
+ a9a_test LATERAL <span class="hljs-keyword">VIEW</span> explode(add_bias(features)) t <span class="hljs-keyword">AS</span> feature
+)
+<span class="hljs-keyword">select</span>
+ t.<span class="hljs-keyword">rowid</span>,
+ sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) <span class="hljs-keyword">as</span> prob,
+ (<span class="hljs-keyword">case</span> <span class="hljs-keyword">when</span> sigmoid(<span class="hljs-keyword">sum</span>(m.weight * t.<span class="hljs-keyword">value</span>)) >= <span class="hljs-number">0.5</span> <span class="hljs-keyword">then</span> <span class="hljs-number">1.0</span> <span class="hljs-keyword">else</span> <span class="hljs-number">0.0</span> <span class="hljs-keyword">end</span>) <span class="hljs-keyword">as</span> label
+<span class="hljs-keyword">from</span>
+ exploded t <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span>
+ <span class="hljs-keyword">model</span> m <span class="hljs-keyword">ON</span> (t.feature = m.feature)
+<span class="hljs-keyword">group</span> <span class="hljs-keyword">by</span>
+ t.<span class="hljs-keyword">rowid</span>;
+</code></pre>
+<h1 id="evaluation">Evaluation</h1>
+<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">or</span> <span class="hljs-keyword">replace</span> <span class="hljs-keyword">view</span> submit <span class="hljs-keyword">as</span>
+<span class="hljs-keyword">select</span>
+ t.label <span class="hljs-keyword">as</span> actual,
+ p.label <span class="hljs-keyword">as</span> predicted,
+ p.prob <span class="hljs-keyword">as</span> probability
+<span class="hljs-keyword">from</span>
+ a9a_test t
+ <span class="hljs-keyword">JOIN</span> predict p <span class="hljs-keyword">on</span> (t.<span class="hljs-keyword">rowid</span> = p.<span class="hljs-keyword">rowid</span>);
+
+<span class="hljs-keyword">select</span>
+ <span class="hljs-keyword">sum</span>(<span class="hljs-keyword">if</span>(actual == predicted, <span class="hljs-number">1</span>, <span class="hljs-number">0</span>)) / <span class="hljs-keyword">count</span>(<span class="hljs-number">1</span>) <span class="hljs-keyword">as</span> accuracy
+<span class="hljs-keyword">from</span>
+ submit;
+</code></pre>
+<blockquote>
+<p>0.8462625145875561</p>
+</blockquote>
+<p>The following table shows accuracy for changing optimizer by <code>-loss logistic -opt XXXXXX -reg l1 -iter 30</code> option:</p>
+<table>
+<thead>
+<tr>
+<th style="text-align:center">Optimizer</th>
+<th style="text-align:center">Accuracy</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style="text-align:center">Default (Adagrad+RDA)</td>
+<td style="text-align:center">0.8462625145875561</td>
+</tr>
+<tr>
+<td style="text-align:center">SGD</td>
+<td style="text-align:center">0.8462010932989374</td>
+</tr>
+<tr>
+<td style="text-align:center">Momentum</td>
+<td style="text-align:center">0.8254406977458387</td>
+</tr>
+<tr>
+<td style="text-align:center">Nesterov</td>
+<td style="text-align:center">0.8286346047540077</td>
+</tr>
+<tr>
+<td style="text-align:center">AdaGrad</td>
+<td style="text-align:center">0.850991953811191</td>
+</tr>
+<tr>
+<td style="text-align:center">RMSprop</td>
+<td style="text-align:center">0.8463239358761747</td>
+</tr>
+<tr>
+<td style="text-align:center">RMSpropGraves</td>
+<td style="text-align:center">0.825563540323076</td>
+</tr>
+<tr>
+<td style="text-align:center">AdaDelta</td>
+<td style="text-align:center">0.8492721577298692</td>
+</tr>
+<tr>
+<td style="text-align:center">Adam</td>
+<td style="text-align:center">0.8341625207296849</td>
+</tr>
+<tr>
+<td style="text-align:center">Nadam</td>
+<td style="text-align:center">0.8349609974817271</td>
+</tr>
+<tr>
+<td style="text-align:center">Eve</td>
+<td style="text-align:center">0.8348381549044899</td>
+</tr>
+<tr>
+<td style="text-align:center">AdamHD</td>
+<td style="text-align:center">0.8447269823720902</td>
+</tr>
+</tbody>
+</table>
+<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>Optimizers using momentum need to tune decay rate well.
+Default (Adagrad+RDA), AdaDelta, Adam, and AdamHD is worth trying in my experience.</p></div></div>
+<p><div id="page-footer" class="localized-footer"><hr><!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<p><sub><font color="gray">
+Apache Hivemall is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator.
+</font></sub></p>
+</div></p>
+
+
+ </section>
+
+ </div>
+ <div class="search-results">
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+
+ </div>
+
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+ gitbook.push(function() {
+ gitbook.page.hasChanged({"page":{"title":"General Binary Classifier","level":"6.2.2","depth":2,"next":{"title":"Logistic Regression","level":"6.2.3","depth":2,"path":"binaryclass/a9a_lr.md","ref":"binaryclass/a9a_lr.md","articles":[]},"previous":{"title":"Data Preparation","level":"6.2.1","depth":2,"path":"binaryclass/a9a_dataset.md","ref":"binaryclass/a9a_dataset.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall/"},
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+
[07/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/sitemap.xml
----------------------------------------------------------------------
diff --git a/userguide/sitemap.xml b/userguide/sitemap.xml
index 1984482..704fe4c 100644
--- a/userguide/sitemap.xml
+++ b/userguide/sitemap.xml
@@ -50,12 +50,14 @@
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/general.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/a9a.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/a9a_dataset.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
+<url> <loc>https://hivemall.incubator.apache.org/binaryclass/a9a_generic.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/a9a_lr.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/a9a_minibatch.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20_dataset.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20_pa.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20_scw.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
+<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20_generic.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20_adagrad.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/news20_rf.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/binaryclass/kdd2010a.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
@@ -85,6 +87,7 @@
<url> <loc>https://hivemall.incubator.apache.org/regression/general.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/regression/e2006.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/regression/e2006_dataset.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
+<url> <loc>https://hivemall.incubator.apache.org/regression/e2006_generic.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/regression/e2006_arow.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/regression/kddcup12tr2.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
<url> <loc>https://hivemall.incubator.apache.org/regression/kddcup12tr2_dataset.html</loc> <changefreq>weekly</changefreq> <priority>0.5</priority> </url>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/spark/binaryclass/a9a_df.html
----------------------------------------------------------------------
diff --git a/userguide/spark/binaryclass/a9a_df.html b/userguide/spark/binaryclass/a9a_df.html
index 0919b23..b824646 100644
--- a/userguide/spark/binaryclass/a9a_df.html
+++ b/userguide/spark/binaryclass/a9a_df.html
@@ -4,7 +4,7 @@
<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>a9a tutorial for DataFrame · Hivemall User Manual</title>
+ <title>a9a Tutorial for DataFrame · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../../binaryclass/a9a_generic.html">
- <a href="../../binaryclass/a9a_lr.html">
+ <a href="../../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../../binaryclass/a9a_lr.html">
+
+ <a href="../../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../../binaryclass/a9a_minibatch.html">
<a href="../../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../../binaryclass/news20_generic.html">
- <a href="../../binaryclass/news20_adagrad.html">
+ <a href="../../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../../binaryclass/news20_adagrad.html">
+
+ <a href="../../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../../binaryclass/news20_rf.html">
<a href="../../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../../regression/e2006_generic.html">
- <a href="../../regression/e2006_arow.html">
+ <a href="../../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../../regression/e2006_arow.html">
+
+ <a href="../../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href="../.." >a9a tutorial for DataFrame</a>
+ <a href="../.." >a9a Tutorial for DataFrame</a>
</h1>
</div>
@@ -2437,7 +2482,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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@@ -2467,7 +2512,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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index f75088b..006cf89 100644
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<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>a9a tutorial for SQL · Hivemall User Manual</title>
+ <title>a9a Tutorial for SQL · Hivemall User Manual</title>
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@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../../binaryclass/a9a_lr.html">
+ <a href="../../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../../binaryclass/a9a_lr.html">
+
+ <a href="../../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
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</li>
- <li class="chapter " data-level="6.2.3" data-path="../../binaryclass/a9a_minibatch.html">
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<a href="../../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../../binaryclass/news20_adagrad.html">
+ <a href="../../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../../binaryclass/news20_adagrad.html">
+
+ <a href="../../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
- <li class="chapter " data-level="6.3.5" data-path="../../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../../binaryclass/news20_rf.html">
<a href="../../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
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<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
- <li class="chapter " data-level="8.2.2" data-path="../../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../../regression/e2006_generic.html">
- <a href="../../regression/e2006_arow.html">
+ <a href="../../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../../regression/e2006_arow.html">
+
+ <a href="../../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
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<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href="../.." >a9a tutorial for SQL</a>
+ <a href="../.." >a9a Tutorial for SQL</a>
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index 68ebc2d..8c0fd58 100644
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<b>6.2.1.</b>
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+ Data Preparation
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<b>6.2.2.</b>
+ General Binary Classifier
+
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+
+
+
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+
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+
Logistic Regression
</a>
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<a href="../../binaryclass/a9a_minibatch.html">
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+ <b>6.2.4.</b>
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+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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<b>6.3.4.</b>
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+
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+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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<a href="../../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
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<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
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<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../../regression/e2006_arow.html">
+ <a href="../../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../../regression/e2006_arow.html">
+
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+
+
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+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2372,7 +2417,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2320,36 +2365,41 @@
<!-- toc --><div id="toc" class="toc">
<ul>
-<li><a href="#udf-preparation">UDF preparation</a></li>
+<li><a href="#adagradrda">AdaGradRDA</a><ul>
<li><a href="#model-building">model building</a></li>
<li><a href="#prediction">prediction</a></li>
<li><a href="#evaluation">evaluation</a></li>
+</ul>
+</li>
+<li><a href="#adagrad">AdaGrad</a><ul>
<li><a href="#model-building-1">model building</a></li>
<li><a href="#prediction-1">prediction</a></li>
<li><a href="#evaluation-1">evaluation</a></li>
+</ul>
+</li>
+<li><a href="#adadelta">AdaDelta</a><ul>
<li><a href="#model-building-2">model building</a></li>
<li><a href="#prediction-2">prediction</a></li>
<li><a href="#evaluation-2">evaluation</a></li>
</ul>
+</li>
+</ul>
</div><!-- tocstop -->
-<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>This feature is supported since Hivemall <code>v0.3-beta2</code> or later.</p></div></div>
-<h2 id="udf-preparation">UDF preparation</h2>
-<pre><code>add jar ./tmp/hivemall-with-dependencies.jar;
-source ./tmp/define-all.hive;
-
-use news20;
-</code></pre><h1 id="adagradrda">[AdaGradRDA]</h1>
+<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p><code>train_adagrad()</code> became deprecated since v0.5.0 release. Use smarter <a href="a9a_generic.html">general classifier</a> instead.</p></div></div>
+<h1 id="adagradrda">AdaGradRDA</h1>
<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>The current AdaGradRDA implmenetation can only be applied to classification, not to regression, because it uses hinge loss for the loss function.</p></div></div>
<h2 id="model-building">model building</h2>
-<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_adagrad_rda_model1;
+<pre><code class="lang-sql"><span class="hljs-keyword">use</span> news20;
+
+<span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_adagrad_rda_model1;
<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> news20b_adagrad_rda_model1 <span class="hljs-keyword">as</span>
<span class="hljs-keyword">select</span>
feature,
voted_avg(weight) <span class="hljs-keyword">as</span> weight
<span class="hljs-keyword">from</span>
(<span class="hljs-keyword">select</span>
- train_adagrad_rda(addBias(features),label) <span class="hljs-keyword">as</span> (feature,weight)
+ train_adagrad_rda(add_bias(features),label) <span class="hljs-keyword">as</span> (feature,weight)
<span class="hljs-keyword">from</span>
news20b_train_x3
) t
@@ -2384,8 +2434,8 @@ use news20;
<p>SCW1 0.9661729383506805 </p>
<p>ADAGRAD+RDA 0.9677742193755005</p>
</blockquote>
-<h1 id="adagrad">[AdaGrad]</h1>
-<p><em>Note that AdaGrad is better suited for a regression problem because the current implementation only support logistic loss.</em></p>
+<h1 id="adagrad">AdaGrad</h1>
+<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>AdaGrad is better suited for a binary classification problem because the current implementation only support logistic loss.</p></div></div>
<h2 id="model-building">model building</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_adagrad_model1;
<span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> news20b_adagrad_model1 <span class="hljs-keyword">as</span>
@@ -2394,7 +2444,7 @@ use news20;
voted_avg(weight) <span class="hljs-keyword">as</span> weight
<span class="hljs-keyword">from</span>
(<span class="hljs-keyword">select</span>
- adagrad(addBias(features),convert_label(label)) <span class="hljs-keyword">as</span> (feature,weight)
+ train_adagrad_regr(add_bias(features),convert_label(label)) <span class="hljs-keyword">as</span> (feature,weight)
<span class="hljs-keyword">from</span>
news20b_train_x3
) t
@@ -2428,7 +2478,7 @@ use news20;
<blockquote>
<p>0.9549639711769415 (adagrad)</p>
</blockquote>
-<h1 id="adadelta">[AdaDelta]</h1>
+<h1 id="adadelta">AdaDelta</h1>
<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p>AdaDelta can only be applied for regression problem because the current implementation only support logistic loss.</p></div></div>
<h2 id="model-building">model building</h2>
<pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> news20b_adadelta_model1;
@@ -2438,7 +2488,7 @@ use news20;
voted_avg(weight) <span class="hljs-keyword">as</span> weight
<span class="hljs-keyword">from</span>
(<span class="hljs-keyword">select</span>
- adadelta(addBias(features),convert_label(label)) <span class="hljs-keyword">as</span> (feature,weight)
+ adadelta(add_bias(features),convert_label(label)) <span class="hljs-keyword">as</span> (feature,weight)
<span class="hljs-keyword">from</span>
news20b_train_x3
) t
@@ -2528,7 +2578,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.3.4","depth":2,"next":{"title":"Random Forest","level":"6.3.5","depth":2,"path":"binaryclass/news20_rf.md","ref":"binaryclass/news20_rf.md","articles":[]},"previous":{"title":"CW, AROW, SCW","level":"6.3.3","depth":2,"path":"binaryclass/news20_scw.md","ref":"binaryclass/news20_scw.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/incubator-hivemall/"},"
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,"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"https://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"path":"binaryclass/news20_adagrad.md","mtime":"2018-10-18T10:26:56.676Z","type":"markdown"},"gitbook":{"version":"3.2.3","time":"2018-11-13T09:32:29.643Z"},"basePath":"..","book":{"language":""}});
+ gitbook.page.hasChanged({"page":{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.3.5","depth":2,"next":{"title":"Random Forest","level":"6.3.6","depth":2,"path":"binaryclass/news20_rf.md","ref":"binaryclass/news20_rf.md","articles":[]},"previous":{"title":"General Binary Classifier","level":"6.3.4","depth":2,"path":"binaryclass/news20_generic.md","ref":"binaryclass/news20_generic.md","articles":[]},"dir":"ltr"},"config":{"plugins":["theme-api","edit-link","github","splitter","sitemap","etoc","callouts","toggle-chapters","anchorjs","codeblock-filename","expandable-chapters","multipart","codeblock-filename","katex","emphasize","localized-footer"],"styles":{"website":"styles/website.css","pdf":"styles/pdf.css","epub":"styles/epub.css","mobi":"styles/mobi.css","ebook":"styles/ebook.css","print":"styles/print.css"},"pluginsConfig":{"emphasize":{},"callouts":{},"etoc":{"h2lb":3,"header":1,"maxdepth":3,"mindepth":1,"notoc":true},"github":{"url":"https://github.com/apache/inc
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"},"showLevel":true},"anchorjs":{"selector":"h1,h2,h3,*:not(.callout) > h4,h5"},"toggle-chapters":{},"expandable-chapters":{}},"theme":"default","pdf":{"pageNumbers":true,"fontSize":12,"fontFamily":"Arial","paperSize":"a4","chapterMark":"pagebreak","pageBreaksBefore":"/","margin":{"right":62,"left":62,"top":56,"bottom":56}},"structure":{"langs":"LANGS.md","readme":"README.md","glossary":"GLOSSARY.md","summary":"SUMMARY.md"},"variables":{},"title":"Hivemall User Manual","links":{"sidebar":{"<i class=\"fa fa-home\"></i> Home":"https://hivemall.incubator.apache.org/"}},"gitbook":"3.x.x","description":"User Manual for Apache Hivemall"},"file":{"path":"binaryclass/news20_adagrad.md","mtime":"2018-12-26T10:16:03.079Z","type":"markdown"},"gitbook":{"version":"3.2.3","time":"2018-12-26T10:20:07.153Z"},"basePath":"..","book":{"language":""}});
});
</script>
</div>
@@ -2558,7 +2608,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/binaryclass/news20_dataset.html
----------------------------------------------------------------------
diff --git a/userguide/binaryclass/news20_dataset.html b/userguide/binaryclass/news20_dataset.html
index 6b26de4..26537ad 100644
--- a/userguide/binaryclass/news20_dataset.html
+++ b/userguide/binaryclass/news20_dataset.html
@@ -4,7 +4,7 @@
<head>
<meta charset="UTF-8">
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
- <title>Data preparation · Hivemall User Manual</title>
+ <title>Data Preparation · Hivemall User Manual</title>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="description" content="">
<meta name="generator" content="GitBook 3.2.3">
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="a9a_generic.html">
- <a href="a9a_lr.html">
+ <a href="a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="a9a_minibatch.html">
<a href="a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="news20_generic.html">
- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="news20_rf.html">
<a href="news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2284,7 +2329,7 @@
<!-- Title -->
<h1>
<i class="fa fa-circle-o-notch fa-spin"></i>
- <a href=".." >Data preparation</a>
+ <a href=".." >Data Preparation</a>
</h1>
</div>
@@ -2352,11 +2397,6 @@ hadoop fs -copyFromLocal news20.test.t /dataset/news20-binary/test
<pre><code class="lang-sql"><span class="hljs-keyword">create</span> <span class="hljs-keyword">database</span> news20;
<span class="hljs-keyword">use</span> news20;
-<span class="hljs-keyword">delete</span> jar /home/myui/tmp/hivemall.jar;
-add jar /home/myui/tmp/hivemall.jar;
-
-source /home/myui/tmp/define-all.hive;
-
<span class="hljs-keyword">Create</span> <span class="hljs-keyword">external</span> <span class="hljs-keyword">table</span> news20b_train (
<span class="hljs-keyword">rowid</span> <span class="hljs-built_in">int</span>,
label <span class="hljs-built_in">int</span>,
@@ -2375,10 +2415,10 @@ source /home/myui/tmp/define-all.hive;
<span class="hljs-keyword">select</span>
*
<span class="hljs-keyword">from</span> (
-<span class="hljs-keyword">select</span>
- amplify(<span class="hljs-number">3</span>, *) <span class="hljs-keyword">as</span> (<span class="hljs-keyword">rowid</span>, label, features)
-<span class="hljs-keyword">from</span>
- news20b_train
+ <span class="hljs-keyword">select</span>
+ amplify(<span class="hljs-number">3</span>, *) <span class="hljs-keyword">as</span> (<span class="hljs-keyword">rowid</span>, label, features)
+ <span class="hljs-keyword">from</span>
+ news20b_train
) t
CLUSTER <span class="hljs-keyword">BY</span> <span class="hljs-keyword">rand</span>(${<span class="hljs-keyword">seed</span>});
@@ -2386,11 +2426,8 @@ CLUSTER <span class="hljs-keyword">BY</span> <span class="hljs-keyword">rand</sp
<span class="hljs-keyword">select</span>
<span class="hljs-keyword">rowid</span>,
label,
- <span class="hljs-keyword">cast</span>(<span class="hljs-keyword">split</span>(feature,<span class="hljs-string">":"</span>)[<span class="hljs-number">0</span>] <span class="hljs-keyword">as</span> <span class="hljs-built_in">int</span>) <span class="hljs-keyword">as</span> feature,
- <span class="hljs-keyword">cast</span>(<span class="hljs-keyword">split</span>(feature,<span class="hljs-string">":"</span>)[<span class="hljs-number">1</span>] <span class="hljs-keyword">as</span> <span class="hljs-built_in">float</span>) <span class="hljs-keyword">as</span> <span class="hljs-keyword">value</span>
- <span class="hljs-comment">-- hivemall v0.3.1 or later</span>
- <span class="hljs-comment">-- extract_feature(feature) as feature,</span>
- <span class="hljs-comment">-- extract_weight(feature) as value</span>
+ extract_feature(feature) <span class="hljs-keyword">as</span> feature,
+ extract_weight(feature) <span class="hljs-keyword">as</span> <span class="hljs-keyword">value</span>
<span class="hljs-keyword">from</span>
news20b_test LATERAL <span class="hljs-keyword">VIEW</span> explode(add_bias(features)) t <span class="hljs-keyword">AS</span> feature;
</code></pre>
@@ -2449,7 +2486,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
- gitbook.page.hasChanged({"page":{"title":"Data preparation","level":"6.3.1","depth":2,"next":{"title":"Perceptron, Passive Aggressive","level":"6.3.2","depth":2,"path":"binaryclass/news20_pa.md","ref":"binaryclass/news20_pa.md","articles":[]},"previous":{"title":"News20 Tutorial","level":"6.3","depth":1,"path":"binaryclass/news20.md","ref":"binaryclass/news20.md","articles":[{"title":"Data preparation","level":"6.3.1","depth":2,"path":"binaryclass/news20_dataset.md","ref":"binaryclass/news20_dataset.md","articles":[]},{"title":"Perceptron, Passive Aggressive","level":"6.3.2","depth":2,"path":"binaryclass/news20_pa.md","ref":"binaryclass/news20_pa.md","articles":[]},{"title":"CW, AROW, SCW","level":"6.3.3","depth":2,"path":"binaryclass/news20_scw.md","ref":"binaryclass/news20_scw.md","articles":[]},{"title":"AdaGradRDA, AdaGrad, AdaDelta","level":"6.3.4","depth":2,"path":"binaryclass/news20_adagrad.md","ref":"binaryclass/news20_adagrad.md","articles":[]},{"title":"Random
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</script>
</div>
@@ -2479,7 +2516,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
[22/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/eval/lr_datagen.html
----------------------------------------------------------------------
diff --git a/userguide/eval/lr_datagen.html b/userguide/eval/lr_datagen.html
index 2dcd713..88edbf3 100644
--- a/userguide/eval/lr_datagen.html
+++ b/userguide/eval/lr_datagen.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
</a>
@@ -995,14 +1010,14 @@
</li>
- <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_minibatch.html">
+ <li class="chapter " data-level="6.2.4" data-path="../binaryclass/a9a_minibatch.html">
<a href="../binaryclass/a9a_minibatch.html">
- <b>6.2.3.</b>
+ <b>6.2.4.</b>
- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
@@ -1038,7 +1053,7 @@
<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
+ <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_generic.html">
- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
@@ -1091,12 +1121,12 @@
</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
+ <li class="chapter " data-level="6.3.6" data-path="../binaryclass/news20_rf.html">
<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1567,13 +1597,28 @@
</li>
- <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_arow.html">
+ <li class="chapter " data-level="8.2.2" data-path="../regression/e2006_generic.html">
- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.3" data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1749,7 +1794,7 @@
<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
@@ -1764,7 +1809,7 @@
<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1830,7 +1875,7 @@
<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
@@ -1890,7 +1935,7 @@
<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
+ 10-fold Cross Validation (Matrix Factorization)
</a>
@@ -2080,7 +2125,7 @@
<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
@@ -2095,7 +2140,7 @@
<b>13.2.2.</b>
- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2460,7 +2505,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
<script>
var gitbook = gitbook || [];
gitbook.push(function() {
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@@ -2490,7 +2535,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
- <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.1/anchor.min.js"></script>
+ <script src="../gitbook/gitbook-plugin-anchorjs/anchor.min.js"></script>
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d9012d92/userguide/eval/multilabel_classification_measures.html
----------------------------------------------------------------------
diff --git a/userguide/eval/multilabel_classification_measures.html b/userguide/eval/multilabel_classification_measures.html
index bf3a34a..79e934d 100644
--- a/userguide/eval/multilabel_classification_measures.html
+++ b/userguide/eval/multilabel_classification_measures.html
@@ -972,7 +972,7 @@
<b>6.2.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -980,13 +980,28 @@
</li>
- <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_lr.html">
+ <li class="chapter " data-level="6.2.2" data-path="../binaryclass/a9a_generic.html">
- <a href="../binaryclass/a9a_lr.html">
+ <a href="../binaryclass/a9a_generic.html">
<b>6.2.2.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="../binaryclass/a9a_lr.html">
+
+ <a href="../binaryclass/a9a_lr.html">
+
+
+ <b>6.2.3.</b>
+
Logistic Regression
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<b>6.3.1.</b>
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+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_adagrad.html">
+
+ <a href="../binaryclass/news20_adagrad.html">
+
+
+ <b>6.3.5.</b>
+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
- <li class="chapter " data-level="6.3.5" data-path="../binaryclass/news20_rf.html">
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<a href="../binaryclass/news20_rf.html">
- <b>6.3.5.</b>
+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
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</a>
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<b>8.2.1.</b>
- Data preparation
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</a>
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<b>8.2.2.</b>
+ General Regessor
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+
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Passive Aggressive, AROW
</a>
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<b>8.3.1.</b>
- Data preparation
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</a>
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<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.2.2.</b>
- LSH/MinHash and Jaccard similarity
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</a>
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<b>9.2.3.</b>
- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
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<b>9.3.5.</b>
- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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<b>9.3.6.</b>
- 10-fold cross validation (Matrix Factorization)
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</a>
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<b>13.2.1.</b>
- a9a tutorial for DataFrame
+ a9a Tutorial for DataFrame
</a>
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<b>13.2.2.</b>
- a9a tutorial for SQL
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</a>
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<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
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</a>
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<b>13.4.</b>
- Generic features
+ Generic Features
</a>
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<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
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<b>13.4.2.</b>
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----------------------------------------------------------------------
diff --git a/userguide/eval/rank.html b/userguide/eval/rank.html
index 12395e7..a408314 100644
--- a/userguide/eval/rank.html
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<b>6.2.1.</b>
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<b>6.2.2.</b>
+ General Binary Classifier
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+ </a>
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+
+
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+
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+
+ <a href="../binaryclass/a9a_lr.html">
+
+
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+
Logistic Regression
</a>
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<a href="../binaryclass/a9a_minibatch.html">
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- Mini-batch gradient descent
+ Mini-batch Gradient Descent
</a>
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<b>6.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1076,13 +1091,28 @@
</li>
- <li class="chapter " data-level="6.3.4" data-path="../binaryclass/news20_adagrad.html">
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- <a href="../binaryclass/news20_adagrad.html">
+ <a href="../binaryclass/news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
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+
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+
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+
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+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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</li>
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<a href="../binaryclass/news20_rf.html">
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+ <b>6.3.6.</b>
Random Forest
@@ -1134,7 +1164,7 @@
<b>6.4.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1185,7 +1215,7 @@
<b>6.5.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1236,7 +1266,7 @@
<b>6.6.1.</b>
- Data pareparation
+ Data Pareparation
</a>
@@ -1302,7 +1332,7 @@
<b>6.8.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1360,7 +1390,7 @@
<b>7.1.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1375,7 +1405,7 @@
<b>7.1.2.</b>
- Data preparation for one-vs-the-rest classifiers
+ Data Preparation for one-vs-the-rest classifiers
</a>
@@ -1435,7 +1465,7 @@
<b>7.1.6.</b>
- one-vs-the-rest classifier
+ one-vs-the-rest Classifier
</a>
@@ -1559,7 +1589,7 @@
<b>8.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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</li>
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- <a href="../regression/e2006_arow.html">
+ <a href="../regression/e2006_generic.html">
<b>8.2.2.</b>
+ General Regessor
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+ </a>
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+
+
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+
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+
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+
+
+ <b>8.2.3.</b>
+
Passive Aggressive, AROW
</a>
@@ -1610,7 +1655,7 @@
<b>8.3.1.</b>
- Data preparation
+ Data Preparation
</a>
@@ -1698,7 +1743,7 @@
<b>9.1.1.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1734,7 +1779,7 @@
<b>9.2.1.</b>
- Data preparation
+ Data Preparation
</a>
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- LSH/MinHash and Jaccard similarity
+ LSH/MinHash and Jaccard Similarity
</a>
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- LSH/MinHash and brute-force search
+ LSH/MinHash and Brute-force Search
</a>
@@ -1815,7 +1860,7 @@
<b>9.3.1.</b>
- Data preparation
+ Data Preparation
</a>
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<b>9.3.2.</b>
- Item-based collaborative filtering
+ Item-based Collaborative Filtering
</a>
@@ -1875,7 +1920,7 @@
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- SLIM for fast top-k recommendation
+ SLIM for fast top-k Recommendation
</a>
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</a>
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<b>13.2.1.</b>
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</a>
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- a9a tutorial for SQL
+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
<b>13.3.1.</b>
- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
@@ -2146,7 +2191,7 @@
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- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
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- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
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- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
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+ Other Utility Functions
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<b>6.2.2.</b>
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Random Forest
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<b>6.5.1.</b>
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</a>
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<b>7.1.1.</b>
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<b>6.2.2.</b>
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Logistic Regression
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</a>
@@ -2146,7 +2191,7 @@
<b>13.3.2.</b>
- E2006-tfidf regression tutorial for SQL
+ E2006-tfidf Regression Tutorial for SQL
</a>
@@ -2166,7 +2211,7 @@
<b>13.4.</b>
- Generic features
+ Generic Features
</a>
@@ -2182,7 +2227,7 @@
<b>13.4.1.</b>
- Top-k join processing
+ Top-k Join Processing
</a>
@@ -2197,7 +2242,7 @@
<b>13.4.2.</b>
- Other utility functions
+ Other Utility Functions
</a>
@@ -2614,7 +2659,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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