org.apache.spark.ml.feature

Class VectorIndexerModel

java.lang.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, Identifiable, MLWritable

public class VectorIndexerModel
extends Model<VectorIndexerModel>
implements MLWritable

:: 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

Methods

Modifier and Type	Method and Description
scala.collection.immutable.Map<java.lang.Object,scala.collection.immutable.Map<java.lang.Object,java.lang.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<java.lang.Integer,java.util.Map<java.lang.Double,java.lang.Integer>>	javaCategoryMaps() Java-friendly version of categoryMaps
static VectorIndexerModel	load(java.lang.String path)
IntParam	maxCategories() Threshold for the number of values a categorical feature can take.
int	numFeatures()
static MLReader<VectorIndexerModel>	read()
VectorIndexerModel	setInputCol(java.lang.String value)
VectorIndexerModel	setOutputCol(java.lang.String value)
DataFrame	transform(DataFrame dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
MLWriter	write() Returns an MLWriter instance for this ML instance.

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 org.apache.spark.ml.PipelineStage

transformSchema

Methods inherited from class java.lang.Object

clone, equals, finalize, 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, shouldOwn, validateParams

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString

Methods inherited from interface org.apache.spark.ml.util.MLWritable

save

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

read

public static MLReader<VectorIndexerModel> read()

load

public static VectorIndexerModel load(java.lang.String path)

uid

public java.lang.String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

numFeatures

public int numFeatures()

categoryMaps

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

javaCategoryMaps

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

Java-friendly version of categoryMaps

setInputCol

public VectorIndexerModel setInputCol(java.lang.String value)

setOutputCol

public VectorIndexerModel setOutputCol(java.lang.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()

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

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()