org.apache.spark.ml.feature
Class VectorIndexerModel

Object
  org.apache.spark.ml.PipelineStage
      org.apache.spark.ml.Transformer
          org.apache.spark.ml.Model<VectorIndexerModel>
              org.apache.spark.ml.feature.VectorIndexerModel

All Implemented Interfaces:

java.io.Serializable, Logging, Params

public class VectorIndexerModel
extends Model<VectorIndexerModel>

:: Experimental :: Transform categorical features to use 0-based indices instead of their original values. - Categorical features are mapped to indices. - Continuous features (columns) are left unchanged. This also appends metadata to the output column, marking features as Numeric (continuous), Nominal (categorical), or Binary (either continuous or categorical). Non-ML metadata is not carried over from the input to the output column.

This maintains vector sparsity.

param: numFeatures Number of features, i.e., length of Vectors which this transforms param: categoryMaps Feature value index. Keys are categorical feature indices (column indices). Values are maps from original features values to 0-based category indices. If a feature is not in this map, it is treated as continuous.

See Also:

Serialized Form

Method Summary

scala.collection.immutable.Map<Object,scala.collection.immutable.Map<Object,Object>>	categoryMaps()
VectorIndexerModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
int	getMaxCategories()
java.util.Map<Integer,java.util.Map<Double,Integer>>	javaCategoryMaps() Java-friendly version of categoryMaps
IntParam	maxCategories() Threshold for the number of values a categorical feature can take.
int	numFeatures()
VectorIndexerModel	setInputCol(String value)
VectorIndexerModel	setOutputCol(String value)
DataFrame	transform(DataFrame dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid()

Methods inherited from class org.apache.spark.ml.Model

hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer

transform, transform, transform

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, setDefault, shouldOwn, validateParams

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Method Detail

uid

public String uid()

numFeatures

public int numFeatures()

categoryMaps

public scala.collection.immutable.Map<Object,scala.collection.immutable.Map<Object,Object>> categoryMaps()

javaCategoryMaps

public java.util.Map<Integer,java.util.Map<Double,Integer>> javaCategoryMaps()

Java-friendly version of categoryMaps

setInputCol

public VectorIndexerModel setInputCol(String value)

setOutputCol

public VectorIndexerModel setOutputCol(String value)

transform

public DataFrame transform(DataFrame dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Derives the output schema from the input schema.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public VectorIndexerModel copy(ParamMap extra)

Description copied from interface: Params

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.

Specified by:

copy in interface Params

Specified by:

copy in class Model<VectorIndexerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

maxCategories

public IntParam maxCategories()

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.

(default = 20)

Returns:

(undocumented)

getMaxCategories

public int getMaxCategories()