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Posted to commits@hivemall.apache.org by my...@apache.org on 2018/12/26 10:23:11 UTC
[23/33] incubator-hivemall-site git commit: Update tutorial for
general classifier/regressor
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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<b>9.3.5.</b>
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- 10-fold cross validation (Matrix Factorization)
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<b>13.2.1.</b>
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- E2006-tfidf regression tutorial for DataFrame
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- E2006-tfidf regression tutorial for SQL
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</a>
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index 9aea0ad..9540269 100644
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<b>6.2.1.</b>
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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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+
+
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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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<b>6.3.4.</b>
+ General Binary Classifier
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+
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AdaGradRDA, AdaGrad, AdaDelta
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Random Forest
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<b>6.4.1.</b>
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+ Data Preparation
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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>
- 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>
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+ Data Preparation for one-vs-the-rest classifiers
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<b>7.1.6.</b>
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<b>8.2.1.</b>
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+ Data Preparation
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<b>9.1.1.</b>
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+ Item-based Collaborative Filtering
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<b>9.2.1.</b>
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+ Item-based Collaborative Filtering
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+ a9a Tutorial for SQL
</a>
@@ -2131,7 +2176,7 @@
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- E2006-tfidf regression tutorial for DataFrame
+ E2006-tfidf Regression Tutorial for DataFrame
</a>
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+ E2006-tfidf Regression Tutorial for SQL
</a>
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- Generic features
+ Generic Features
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+ Top-k Join Processing
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