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<div class="subTitle">org.apache.spark.mllib.feature</div>
<h2 title="Class Word2Vec" class="title">Class Word2Vec</h2>
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<li>java.lang.Object</li>
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<li>org.apache.spark.mllib.feature.Word2Vec</li>
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<pre>public class <span class="strong">Word2Vec</span>
extends java.lang.Object
implements scala.Serializable, <a href="../../../../../org/apache/spark/Logging.html" title="interface in org.apache.spark">Logging</a></pre>
<div class="block">:: Experimental ::
Word2Vec creates vector representation of words in a text corpus.
The algorithm first constructs a vocabulary from the corpus
and then learns vector representation of words in the vocabulary.
The vector representation can be used as features in
natural language processing and machine learning algorithms.
<p>
We used skip-gram model in our implementation and hierarchical softmax
method to train the model. The variable names in the implementation
matches the original C implementation.
<p>
For original C implementation, see https://code.google.com/p/word2vec/
For research papers, see
Efficient Estimation of Word Representations in Vector Space
and
Distributed Representations of Words and Phrases and their Compositionality.</div>
<dl><dt><span class="strong">See Also:</span></dt><dd><a href="../../../../../serialized-form.html#org.apache.spark.mllib.feature.Word2Vec">Serialized Form</a></dd></dl>
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<td class="colOne"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#Word2Vec()">Word2Vec</a></strong>()</code> </td>
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<th class="colLast" scope="col">Method and Description</th>
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<td class="colFirst"><code><S extends java.lang.Iterable<java.lang.String>> <br><a href="../../../../../org/apache/spark/mllib/feature/Word2VecModel.html" title="class in org.apache.spark.mllib.feature">Word2VecModel</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#fit(org.apache.spark.api.java.JavaRDD)">fit</a></strong>(<a href="../../../../../org/apache/spark/api/java/JavaRDD.html" title="class in org.apache.spark.api.java">JavaRDD</a><S> dataset)</code>
<div class="block">Computes the vector representation of each word in vocabulary (Java version).</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code><S extends scala.collection.Iterable<java.lang.String>> <br><a href="../../../../../org/apache/spark/mllib/feature/Word2VecModel.html" title="class in org.apache.spark.mllib.feature">Word2VecModel</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#fit(org.apache.spark.rdd.RDD)">fit</a></strong>(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><S> dataset)</code>
<div class="block">Computes the vector representation of each word in vocabulary.</div>
</td>
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<tr class="altColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#setLearningRate(double)">setLearningRate</a></strong>(double learningRate)</code>
<div class="block">Sets initial learning rate (default: 0.025).</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#setMinCount(int)">setMinCount</a></strong>(int minCount)</code>
<div class="block">Sets minCount, the minimum number of times a token must appear to be included in the word2vec
model's vocabulary (default: 5).</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#setNumIterations(int)">setNumIterations</a></strong>(int numIterations)</code>
<div class="block">Sets number of iterations (default: 1), which should be smaller than or equal to number of
partitions.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#setNumPartitions(int)">setNumPartitions</a></strong>(int numPartitions)</code>
<div class="block">Sets number of partitions (default: 1).</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#setSeed(long)">setSeed</a></strong>(long seed)</code>
<div class="block">Sets random seed (default: a random long integer).</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html#setVectorSize(int)">setVectorSize</a></strong>(int vectorSize)</code>
<div class="block">Sets vector size (default: 100).</div>
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<code><a href="../../../../../org/apache/spark/Logging.html#initializeIfNecessary()">initializeIfNecessary</a>, <a href="../../../../../org/apache/spark/Logging.html#initializeLogging()">initializeLogging</a>, <a href="../../../../../org/apache/spark/Logging.html#isTraceEnabled()">isTraceEnabled</a>, <a href="../../../../../org/apache/spark/Logging.html#log_()">log_</a>, <a href="../../../../../org/apache/spark/Logging.html#log()">log</a>, <a href="../../../../../org/apache/spark/Logging.html#logDebug(scala.Function0)">logDebug</a>, <a href="../../../../../org/apache/spark/Logging.html#logDebug(scala.Function0, java.lang.Throwable)">logDebug</a>, <a href="../../../../../org/apache/spark/Logging.html#logError(scala.Function0)">logError</a>, <a href="../../../../../org/apache/spark/Logging.html#logError(scala.Function0, java.lang.Throwable)">logError</a>, <a href="../../../../../org/apache/spark/Logging.html#logInfo(scala.Function0)">logInfo</a>, <a href="../../../../../org/apache/spark/Logging.html#logInfo(scala.Function0, java.lang.Throwable)">logInfo</a>, <a href="../../../../../org/apache/spark/Logging.html#logName()">logName</a>, <a href="../../../../../org/apache/spark/Logging.html#logTrace(scala.Function0)">logTrace</a>, <a href="../../../../../org/apache/spark/Logging.html#logTrace(scala.Function0, java.lang.Throwable)">logTrace</a>, <a href="../../../../../org/apache/spark/Logging.html#logWarning(scala.Function0)">logWarning</a>, <a href="../../../../../org/apache/spark/Logging.html#logWarning(scala.Function0, java.lang.Throwable)">logWarning</a></code></li>
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<pre>public Word2Vec()</pre>
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<pre>public <a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a> setVectorSize(int vectorSize)</pre>
<div class="block">Sets vector size (default: 100).</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>vectorSize</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a> setLearningRate(double learningRate)</pre>
<div class="block">Sets initial learning rate (default: 0.025).</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>learningRate</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a> setNumPartitions(int numPartitions)</pre>
<div class="block">Sets number of partitions (default: 1). Use a small number for accuracy.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>numPartitions</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a> setNumIterations(int numIterations)</pre>
<div class="block">Sets number of iterations (default: 1), which should be smaller than or equal to number of
partitions.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>numIterations</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a> setSeed(long seed)</pre>
<div class="block">Sets random seed (default: a random long integer).</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>seed</code> - (undocumented)</dd>
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<pre>public <a href="../../../../../org/apache/spark/mllib/feature/Word2Vec.html" title="class in org.apache.spark.mllib.feature">Word2Vec</a> setMinCount(int minCount)</pre>
<div class="block">Sets minCount, the minimum number of times a token must appear to be included in the word2vec
model's vocabulary (default: 5).</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>minCount</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <S extends scala.collection.Iterable<java.lang.String>> <a href="../../../../../org/apache/spark/mllib/feature/Word2VecModel.html" title="class in org.apache.spark.mllib.feature">Word2VecModel</a> fit(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><S> dataset)</pre>
<div class="block">Computes the vector representation of each word in vocabulary.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>dataset</code> - an RDD of words</dd>
<dt><span class="strong">Returns:</span></dt><dd>a Word2VecModel</dd></dl>
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<pre>public <S extends java.lang.Iterable<java.lang.String>> <a href="../../../../../org/apache/spark/mllib/feature/Word2VecModel.html" title="class in org.apache.spark.mllib.feature">Word2VecModel</a> fit(<a href="../../../../../org/apache/spark/api/java/JavaRDD.html" title="class in org.apache.spark.api.java">JavaRDD</a><S> dataset)</pre>
<div class="block">Computes the vector representation of each word in vocabulary (Java version).</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>dataset</code> - a JavaRDD of words</dd>
<dt><span class="strong">Returns:</span></dt><dd>a Word2VecModel</dd></dl>
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