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Posted to commits@hivemall.apache.org by my...@apache.org on 2018/12/26 10:23:13 UTC
[25/33] 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/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 || [];
gitbook.push(function() {
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<b>6.2.1.</b>
- Data preparation
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</a>
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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">
+
+
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+
Logistic Regression
</a>
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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 @@
</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
+
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+
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+
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+
+ <a href="news20_adagrad.html">
+
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+
AdaGradRDA, AdaGrad, AdaDelta
</a>
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<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>
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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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+
+
+
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+
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+
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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>
@@ -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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@@ -97,7 +97,7 @@
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@@ -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>
+
+
+
+ </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>
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- <a href="news20_adagrad.html">
+ <a href="news20_generic.html">
<b>6.3.4.</b>
+ General Binary Classifier
+
+ </a>
+
+
+
+ </li>
+
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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
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@@ -2661,7 +2678,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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