org.apache.spark.ml.feature

Class Word2VecModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<Word2VecModel>

org.apache.spark.ml.feature.Word2VecModel

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable, MLWritable

public class Word2VecModel
extends Model<Word2VecModel>
implements MLWritable

:: Experimental :: Model fitted by Word2Vec.

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
Word2VecModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
DataFrame	findSynonyms(String word, int num) Find "num" number of words closest in similarity to the given word.
DataFrame	findSynonyms(Vector word, int num) Find "num" number of words closest to similarity to the given vector representation of the word.
String	getInputCol()
int	getMaxIter()
int	getMinCount()
int	getNumPartitions()
String	getOutputCol()
long	getSeed()
double	getStepSize()
DataFrame	getVectors() Returns a dataframe with two fields, "word" and "vector", with "word" being a String and and the vector the DenseVector that it is mapped to.
int	getVectorSize()
int	getWindowSize()
Param<String>	inputCol() Param for input column name.
static Word2VecModel	load(String path)
IntParam	maxIter() Param for maximum number of iterations (>= 0).
IntParam	minCount() The minimum number of times a token must appear to be included in the word2vec model's vocabulary.
IntParam	numPartitions() Number of partitions for sentences of words.
Param<String>	outputCol() Param for output column name.
static MLReader<Word2VecModel>	read()
LongParam	seed() Param for random seed.
Word2VecModel	setInputCol(String value)
Word2VecModel	setOutputCol(String value)
DoubleParam	stepSize() Param for Step size to be used for each iteration of optimization..
DataFrame	transform(DataFrame dataset) Transform a sentence column to a vector column to represent the whole sentence.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.
StructType	validateAndTransformSchema(StructType schema) Validate and transform the input schema.
IntParam	vectorSize() The dimension of the code that you want to transform from words.
IntParam	windowSize() The window size (context words from [-window, window]) default 5.
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 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, 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<Word2VecModel> read()

load

public static Word2VecModel load(String path)

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)

getVectors

public DataFrame getVectors()

Returns a dataframe with two fields, "word" and "vector", with "word" being a String and and the vector the DenseVector that it is mapped to.

Returns:

(undocumented)

findSynonyms

public DataFrame findSynonyms(String word,
                     int num)

Find "num" number of words closest in similarity to the given word. Returns a dataframe with the words and the cosine similarities between the synonyms and the given word.

Parameters:

word - (undocumented)

num - (undocumented)

Returns:

(undocumented)

findSynonyms

public DataFrame findSynonyms(Vector word,
                     int num)

Find "num" number of words closest to similarity to the given vector representation of the word. Returns a dataframe with the words and the cosine similarities between the synonyms and the given word vector.

Parameters:

word - (undocumented)

num - (undocumented)

Returns:

(undocumented)

setInputCol

public Word2VecModel setInputCol(String value)

setOutputCol

public Word2VecModel setOutputCol(String value)

transform

public DataFrame transform(DataFrame dataset)

Transform a sentence column to a vector column to represent the whole sentence. The transform is performed by averaging all word vectors it contains.

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 Word2VecModel 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<Word2VecModel>

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)

vectorSize

public IntParam vectorSize()

The dimension of the code that you want to transform from words. Default: 100

Returns:

(undocumented)

getVectorSize

public int getVectorSize()

windowSize

public IntParam windowSize()

The window size (context words from [-window, window]) default 5.

Returns:

(undocumented)

getWindowSize

public int getWindowSize()

numPartitions

public IntParam numPartitions()

Number of partitions for sentences of words. Default: 1

Returns:

(undocumented)

getNumPartitions

public int getNumPartitions()

minCount

public IntParam minCount()

The minimum number of times a token must appear to be included in the word2vec model's vocabulary. Default: 5

Returns:

(undocumented)

getMinCount

public int getMinCount()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Validate and transform the input schema.

Parameters:

schema - (undocumented)

Returns:

(undocumented)

inputCol

public Param<String> inputCol()

Param for input column name.

Returns:

(undocumented)

getInputCol

public String getInputCol()

outputCol

public Param<String> outputCol()

Param for output column name.

Returns:

(undocumented)

getOutputCol

public String getOutputCol()

maxIter

public IntParam maxIter()

Param for maximum number of iterations (>= 0).

Returns:

(undocumented)

getMaxIter

public int getMaxIter()

stepSize

public DoubleParam stepSize()

Param for Step size to be used for each iteration of optimization..

Returns:

(undocumented)

getStepSize

public double getStepSize()

seed

public LongParam seed()

Param for random seed.

Returns:

(undocumented)

getSeed

public long getSeed()