org.apache.spark.ml.feature

Class HashingTF

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.feature.HashingTF

All Implemented Interfaces:

java.io.Serializable, Logging, Params, HasInputCol, HasNumFeatures, HasOutputCol, DefaultParamsWritable, Identifiable, MLWritable

public class HashingTF
extends Transformer
implements HasInputCol, HasOutputCol, HasNumFeatures, DefaultParamsWritable

Maps a sequence of terms to their term frequencies using the hashing trick. Currently we use Austin Appleby's MurmurHash 3 algorithm (MurmurHash3_x86_32) to calculate the hash code value for the term object. Since a simple modulo is used to transform the hash function to a column index, it is advisable to use a power of two as the numFeatures parameter; otherwise the features will not be mapped evenly to the columns.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
HashingTF()
HashingTF(String uid)

Method Summary

Modifier and Type	Method and Description
BooleanParam	binary() Binary toggle to control term frequency counts.
HashingTF	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
boolean	getBinary()
int	indexOf(Object term) Returns the index of the input term.
Param<String>	inputCol() Param for input column name.
static HashingTF	load(String path)
IntParam	numFeatures() Param for Number of features.
Param<String>	outputCol() Param for output column name.
static MLReader<HashingTF>	read()
HashingTF	setBinary(boolean value)
HashingTF	setInputCol(String value)
HashingTF	setNumFeatures(int value)
HashingTF	setOutputCol(String value)
String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.

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

transform, transform, transform

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

params

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol

getInputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol

getOutputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasNumFeatures

getNumFeatures

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

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

write

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

save

Methods inherited from interface org.apache.spark.internal.Logging

initializeForcefully, initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

HashingTF

public HashingTF(String uid)

HashingTF

public HashingTF()

Method Detail

read

public static MLReader<HashingTF> read()

load

public static HashingTF load(String path)

numFeatures

public final IntParam numFeatures()

Description copied from interface: HasNumFeatures

Param for Number of features. Should be greater than 0.

Specified by:

numFeatures in interface HasNumFeatures

Returns:

(undocumented)

outputCol

public final Param<String> outputCol()

Description copied from interface: HasOutputCol

Param for output column name.

Specified by:

outputCol in interface HasOutputCol

Returns:

(undocumented)

inputCol

public final Param<String> inputCol()

Description copied from interface: HasInputCol

Param for input column name.

Specified by:

inputCol in interface HasInputCol

Returns:

(undocumented)

uid

public 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)

setInputCol

public HashingTF setInputCol(String value)

setOutputCol

public HashingTF setOutputCol(String value)

binary

public BooleanParam binary()

Binary toggle to control term frequency counts. If true, all non-zero counts are set to 1. This is useful for discrete probabilistic models that model binary events rather than integer counts. (default = false)

Returns:

(undocumented)

setNumFeatures

public HashingTF setNumFeatures(int value)

getBinary

public boolean getBinary()

setBinary

public HashingTF setBinary(boolean value)

transform

public Dataset<Row> transform(Dataset<?> 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 ::

Check transform validity and derive the output schema from the input schema.

We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

indexOf

public int indexOf(Object term)

Returns the index of the input term.

Parameters:

term - (undocumented)

Returns:

(undocumented)

copy

public HashingTF 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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Transformer

Parameters:

extra - (undocumented)

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object