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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
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<div class="subTitle">org.apache.spark.ml.feature</div>
<h2 title="Class VectorIndexer" class="title">Class VectorIndexer</h2>
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<li>java.lang.Object</li>
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<pre>public class <span class="strong">VectorIndexer</span>
extends <a href="../../../../../org/apache/spark/ml/Estimator.html" title="class in org.apache.spark.ml">Estimator</a>&lt;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexerModel.html" title="class in org.apache.spark.ml.feature">VectorIndexerModel</a>&gt;</pre>
<div class="block">:: Experimental ::
 Class for indexing categorical feature columns in a dataset of <code>Vector</code>.
 <p>
 This has 2 usage modes:
  - Automatically identify categorical features (default behavior)
     - This helps process a dataset of unknown vectors into a dataset with some continuous
       features and some categorical features. The choice between continuous and categorical
       is based upon a maxCategories parameter.
     - Set maxCategories to the maximum number of categorical any categorical feature should have.
     - E.g.: Feature 0 has unique values {-1.0, 0.0}, and feature 1 values {1.0, 3.0, 5.0}.
       If maxCategories = 2, then feature 0 will be declared categorical and use indices {0, 1},
       and feature 1 will be declared continuous.
  - Index all features, if all features are categorical
     - If maxCategories is set to be very large, then this will build an index of unique
       values for all features.
     - Warning: This can cause problems if features are continuous since this will collect ALL
       unique values to the driver.
     - E.g.: Feature 0 has unique values {-1.0, 0.0}, and feature 1 values {1.0, 3.0, 5.0}.
       If maxCategories >= 3, then both features will be declared categorical.
 <p>
 This returns a model which can transform categorical features to use 0-based indices.
 <p>
 Index stability:
  - This is not guaranteed to choose the same category index across multiple runs.
  - If a categorical feature includes value 0, then this is guaranteed to map value 0 to index 0.
    This maintains vector sparsity.
  - More stability may be added in the future.
 <p>
 TODO: Future extensions: The following functionality is planned for the future:
  - Preserve metadata in transform; if a feature's metadata is already present, do not recompute.
  - Specify certain features to not index, either via a parameter or via existing metadata.
  - Add warning if a categorical feature has only 1 category.
  - Add option for allowing unknown categories.</div>
<dl><dt><span class="strong">See Also:</span></dt><dd><a href="../../../../../serialized-form.html#org.apache.spark.ml.feature.VectorIndexer">Serialized Form</a></dd></dl>
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<div class="block">Helper class for tracking unique values for each feature.</div>
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<td class="colOne"><code><strong><a href="../../../../../org/apache/spark/ml/feature/VectorIndexer.html#VectorIndexer()">VectorIndexer</a></strong>()</code>&nbsp;</td>
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<td class="colFirst"><code>int</code></td>
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<div class="block">:: DeveloperApi ::</div>
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<h3>Methods inherited from interface&nbsp;org.apache.spark.<a href="../../../../../org/apache/spark/Logging.html" title="interface in org.apache.spark">Logging</a></h3>
<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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<h4>VectorIndexer</h4>
<pre>public&nbsp;VectorIndexer(java.lang.String&nbsp;uid)</pre>
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<pre>public&nbsp;VectorIndexer()</pre>
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<pre>public&nbsp;java.lang.String&nbsp;uid()</pre>
<div class="block"><strong>Description copied from interface:&nbsp;<code><a href="../../../../../org/apache/spark/ml/util/Identifiable.html#uid()">Identifiable</a></code></strong></div>
<div class="block">An immutable unique ID for the object and its derivatives.</div>
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<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/spark/ml/util/Identifiable.html#uid()">uid</a></code>&nbsp;in interface&nbsp;<code><a href="../../../../../org/apache/spark/ml/util/Identifiable.html" title="interface in org.apache.spark.ml.util">Identifiable</a></code></dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexer.html" title="class in org.apache.spark.ml.feature">VectorIndexer</a>&nbsp;setMaxCategories(int&nbsp;value)</pre>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexer.html" title="class in org.apache.spark.ml.feature">VectorIndexer</a>&nbsp;setInputCol(java.lang.String&nbsp;value)</pre>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexer.html" title="class in org.apache.spark.ml.feature">VectorIndexer</a>&nbsp;setOutputCol(java.lang.String&nbsp;value)</pre>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexerModel.html" title="class in org.apache.spark.ml.feature">VectorIndexerModel</a>&nbsp;fit(<a href="../../../../../org/apache/spark/sql/DataFrame.html" title="class in org.apache.spark.sql">DataFrame</a>&nbsp;dataset)</pre>
<div class="block"><strong>Description copied from class:&nbsp;<code><a href="../../../../../org/apache/spark/ml/Estimator.html#fit(org.apache.spark.sql.DataFrame)">Estimator</a></code></strong></div>
<div class="block">Fits a model to the input data.</div>
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<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/spark/ml/Estimator.html#fit(org.apache.spark.sql.DataFrame)">fit</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/spark/ml/Estimator.html" title="class in org.apache.spark.ml">Estimator</a>&lt;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexerModel.html" title="class in org.apache.spark.ml.feature">VectorIndexerModel</a>&gt;</code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>dataset</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/sql/types/StructType.html" title="class in org.apache.spark.sql.types">StructType</a>&nbsp;transformSchema(<a href="../../../../../org/apache/spark/sql/types/StructType.html" title="class in org.apache.spark.sql.types">StructType</a>&nbsp;schema)</pre>
<div class="block"><strong>Description copied from class:&nbsp;<code><a href="../../../../../org/apache/spark/ml/PipelineStage.html#transformSchema(org.apache.spark.sql.types.StructType)">PipelineStage</a></code></strong></div>
<div class="block">:: DeveloperApi ::
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 Derives the output schema from the input schema.</div>
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<dd><code><a href="../../../../../org/apache/spark/ml/PipelineStage.html#transformSchema(org.apache.spark.sql.types.StructType)">transformSchema</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/spark/ml/PipelineStage.html" title="class in org.apache.spark.ml">PipelineStage</a></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>schema</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexer.html" title="class in org.apache.spark.ml.feature">VectorIndexer</a>&nbsp;copy(<a href="../../../../../org/apache/spark/ml/param/ParamMap.html" title="class in org.apache.spark.ml.param">ParamMap</a>&nbsp;extra)</pre>
<div class="block"><strong>Description copied from interface:&nbsp;<code><a href="../../../../../org/apache/spark/ml/param/Params.html#copy(org.apache.spark.ml.param.ParamMap)">Params</a></code></strong></div>
<div class="block">Creates a copy of this instance with the same UID and some extra params.
 Subclasses should implement this method and set the return type properly.
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<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/spark/ml/param/Params.html#copy(org.apache.spark.ml.param.ParamMap)">copy</a></code>&nbsp;in interface&nbsp;<code><a href="../../../../../org/apache/spark/ml/param/Params.html" title="interface in org.apache.spark.ml.param">Params</a></code></dd>
<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/spark/ml/Estimator.html#copy(org.apache.spark.ml.param.ParamMap)">copy</a></code>&nbsp;in class&nbsp;<code><a href="../../../../../org/apache/spark/ml/Estimator.html" title="class in org.apache.spark.ml">Estimator</a>&lt;<a href="../../../../../org/apache/spark/ml/feature/VectorIndexerModel.html" title="class in org.apache.spark.ml.feature">VectorIndexerModel</a>&gt;</code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>extra</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd><dt><span class="strong">See Also:</span></dt><dd><code>defaultCopy()</code></dd></dl>
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<pre>public&nbsp;<a href="../../../../../org/apache/spark/ml/param/IntParam.html" title="class in org.apache.spark.ml.param">IntParam</a>&nbsp;maxCategories()</pre>
<div class="block">Threshold for the number of values a categorical feature can take.
 If a feature is found to have > maxCategories values, then it is declared continuous.
 Must be >= 2.
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 (default = 20)</div>
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<pre>public&nbsp;int&nbsp;getMaxCategories()</pre>
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