Word2VecModel#

class pyspark.ml.feature.Word2VecModel(java_model=None)[source]#

Model fitted by Word2Vec.

New in version 1.4.0.

Methods

`clear`(param)	Clears a param from the param map if it has been explicitly set.
`copy`([extra])	Creates a copy of this instance with the same uid and some extra params.
`explainParam`(param)	Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
`explainParams`()	Returns the documentation of all params with their optionally default values and user-supplied values.
`extractParamMap`([extra])	Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
`findSynonyms`(word, num)	Find "num" number of words closest in similarity to "word".
`findSynonymsArray`(word, num)	Find "num" number of words closest in similarity to "word".
`getInputCol`()	Gets the value of inputCol or its default value.
`getMaxIter`()	Gets the value of maxIter or its default value.
`getMaxSentenceLength`()	Gets the value of maxSentenceLength or its default value.
`getMinCount`()	Gets the value of minCount or its default value.
`getNumPartitions`()	Gets the value of numPartitions or its default value.
`getOrDefault`(param)	Gets the value of a param in the user-supplied param map or its default value.
`getOutputCol`()	Gets the value of outputCol or its default value.
`getParam`(paramName)	Gets a param by its name.
`getSeed`()	Gets the value of seed or its default value.
`getStepSize`()	Gets the value of stepSize or its default value.
`getVectorSize`()	Gets the value of vectorSize or its default value.
`getVectors`()	Returns the vector representation of the words as a dataframe with two fields, word and vector.
`getWindowSize`()	Gets the value of windowSize or its default value.
`hasDefault`(param)	Checks whether a param has a default value.
`hasParam`(paramName)	Tests whether this instance contains a param with a given (string) name.
`isDefined`(param)	Checks whether a param is explicitly set by user or has a default value.
`isSet`(param)	Checks whether a param is explicitly set by user.
`load`(path)	Reads an ML instance from the input path, a shortcut of read().load(path).
`read`()	Returns an MLReader instance for this class.
`save`(path)	Save this ML instance to the given path, a shortcut of 'write().save(path)'.
`set`(param, value)	Sets a parameter in the embedded param map.
`setInputCol`(value)	Sets the value of `inputCol`.
`setOutputCol`(value)	Sets the value of `outputCol`.
`transform`(dataset[, params])	Transforms the input dataset with optional parameters.
`write`()	Returns an MLWriter instance for this ML instance.

Attributes

`inputCol`
`maxIter`
`maxSentenceLength`
`minCount`
`numPartitions`
`outputCol`
`params`	Returns all params ordered by name.
`seed`
`stepSize`
`vectorSize`
`windowSize`

Methods Documentation

clear(param)#: Clears a param from the param map if it has been explicitly set.

copy(extra=None)#

Creates a copy of this instance with the same uid and some extra params. This implementation first calls Params.copy and then make a copy of the companion Java pipeline component with extra params. So both the Python wrapper and the Java pipeline component get copied.

Parameters

extradict, optional: Extra parameters to copy to the new instance

Returns

JavaParams: Copy of this instance

explainParam(param)#: Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.

explainParams()#: Returns the documentation of all params with their optionally default values and user-supplied values.

extractParamMap(extra=None)#

Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.

Parameters

extradict, optional: extra param values

Returns

dict: merged param map

findSynonyms(word, num)[source]#: Find “num” number of words closest in similarity to “word”. word can be a string or vector representation. Returns a dataframe with two fields word and similarity (which gives the cosine similarity).

New in version 1.5.0.

findSynonymsArray(word, num)[source]#: Find “num” number of words closest in similarity to “word”. word can be a string or vector representation. Returns an array with two fields word and similarity (which gives the cosine similarity).

New in version 2.3.0.

getInputCol()#: Gets the value of inputCol or its default value.

getMaxIter()#: Gets the value of maxIter or its default value.

getMaxSentenceLength()#: Gets the value of maxSentenceLength or its default value.

New in version 2.0.0.

getMinCount()#: Gets the value of minCount or its default value.

New in version 1.4.0.

getNumPartitions()#: Gets the value of numPartitions or its default value.

New in version 1.4.0.

getOrDefault(param)#: Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.

getOutputCol()#: Gets the value of outputCol or its default value.

getParam(paramName)#: Gets a param by its name.

getSeed()#: Gets the value of seed or its default value.

getStepSize()#: Gets the value of stepSize or its default value.

getVectorSize()#: Gets the value of vectorSize or its default value.

New in version 1.4.0.

getVectors()[source]#: Returns the vector representation of the words as a dataframe with two fields, word and vector.

New in version 1.5.0.

getWindowSize()#: Gets the value of windowSize or its default value.

New in version 2.0.0.

hasDefault(param)#: Checks whether a param has a default value.

hasParam(paramName)#: Tests whether this instance contains a param with a given (string) name.

isDefined(param)#: Checks whether a param is explicitly set by user or has a default value.

isSet(param)#: Checks whether a param is explicitly set by user.

classmethod load(path)#: Reads an ML instance from the input path, a shortcut of read().load(path).

classmethod read()#: Returns an MLReader instance for this class.

save(path)#: Save this ML instance to the given path, a shortcut of ‘write().save(path)’.

set(param, value)#: Sets a parameter in the embedded param map.

setInputCol(value)[source]#: Sets the value of inputCol.

setOutputCol(value)[source]#: Sets the value of outputCol.

transform(dataset, params=None)#

Transforms the input dataset with optional parameters.

New in version 1.3.0.

Parameters

datasetpyspark.sql.DataFrame: input dataset
paramsdict, optional: an optional param map that overrides embedded params.

Returns

pyspark.sql.DataFrame: transformed dataset

write()#: Returns an MLWriter instance for this ML instance.

Attributes Documentation

inputCol = Param(parent='undefined', name='inputCol', doc='input column name.')#

maxIter = Param(parent='undefined', name='maxIter', doc='max number of iterations (>= 0).')#

maxSentenceLength = Param(parent='undefined', name='maxSentenceLength', doc='Maximum length (in words) of each sentence in the input data. Any sentence longer than this threshold will be divided into chunks up to the size.')#

minCount = Param(parent='undefined', name='minCount', doc="the minimum number of times a token must appear to be included in the word2vec model's vocabulary")#

numPartitions = Param(parent='undefined', name='numPartitions', doc='number of partitions for sentences of words')#

outputCol = Param(parent='undefined', name='outputCol', doc='output column name.')#

params#: Returns all params ordered by name. The default implementation uses dir() to get all attributes of type Param.

seed = Param(parent='undefined', name='seed', doc='random seed.')#

stepSize = Param(parent='undefined', name='stepSize', doc='Step size to be used for each iteration of optimization (>= 0).')#

vectorSize = Param(parent='undefined', name='vectorSize', doc='the dimension of codes after transforming from words')#

windowSize = Param(parent='undefined', name='windowSize', doc='the window size (context words from [-window, window]). Default value is 5')#

uid#: A unique id for the object.