org.apache.spark.ml.feature

Class Word2VecModel

java.lang.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

public class Word2VecModel
extends Model<Word2VecModel>

:: 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(java.lang.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.
int	getMinCount()
int	getNumPartitions()
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()
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.
Word2VecModel	setInputCol(java.lang.String value)
Word2VecModel	setOutputCol(java.lang.String value)
DataFrame	transform(DataFrame dataset) Transform a sentence column to a vector column to represent the whole sentence.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.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.

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.Logging

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

Method Detail

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)

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(java.lang.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(java.lang.String value)

setOutputCol

public Word2VecModel setOutputCol(java.lang.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()

vectorSize

public IntParam vectorSize()

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

Returns:

(undocumented)

getVectorSize

public int getVectorSize()

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)