class Word2VecModel extends Model[Word2VecModel] with Word2VecBase with MLWritable
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- Word2VecModel
- MLWritable
- Word2VecBase
- HasSeed
- HasStepSize
- HasMaxIter
- HasOutputCol
- HasInputCol
- Model
- Transformer
- PipelineStage
- Logging
- Params
- Serializable
- Identifiable
- AnyRef
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Parameters
A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.
- final val inputCol: Param[String]
Param for input column name.
Param for input column name.
- Definition Classes
- HasInputCol
- final val maxIter: IntParam
Param for maximum number of iterations (>= 0).
Param for maximum number of iterations (>= 0).
- Definition Classes
- HasMaxIter
- final val maxSentenceLength: IntParam
Sets the maximum length (in words) of each sentence in the input data.
Sets the maximum length (in words) of each sentence in the input data. Any sentence longer than this threshold will be divided into chunks of up to
maxSentenceLength
size. Default: 1000- Definition Classes
- Word2VecBase
- final val minCount: IntParam
The minimum number of times a token must appear to be included in the word2vec model's vocabulary.
The minimum number of times a token must appear to be included in the word2vec model's vocabulary. Default: 5
- Definition Classes
- Word2VecBase
- final val numPartitions: IntParam
Number of partitions for sentences of words.
Number of partitions for sentences of words. Default: 1
- Definition Classes
- Word2VecBase
- final val outputCol: Param[String]
Param for output column name.
Param for output column name.
- Definition Classes
- HasOutputCol
- final val seed: LongParam
Param for random seed.
Param for random seed.
- Definition Classes
- HasSeed
- val stepSize: DoubleParam
Param for Step size to be used for each iteration of optimization (> 0).
Param for Step size to be used for each iteration of optimization (> 0).
- Definition Classes
- HasStepSize
- final val vectorSize: IntParam
The dimension of the code that you want to transform from words.
The dimension of the code that you want to transform from words. Default: 100
- Definition Classes
- Word2VecBase
Members
- implicit class LogStringContext extends AnyRef
- Definition Classes
- Logging
- final def clear(param: Param[_]): Word2VecModel.this.type
Clears the user-supplied value for the input param.
Clears the user-supplied value for the input param.
- Definition Classes
- Params
- def copy(extra: ParamMap): Word2VecModel
Creates a copy of this instance with the same UID and some extra 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()
.- Definition Classes
- Word2VecModel → Model → Transformer → PipelineStage → Params
- Annotations
- @Since("1.4.1")
- def explainParam(param: Param[_]): String
Explains a param.
Explains a param.
- param
input param, must belong to this instance.
- returns
a string that contains the input param name, doc, and optionally its default value and the user-supplied value
- Definition Classes
- Params
- def explainParams(): String
Explains all params of this instance.
Explains all params of this instance. See
explainParam()
.- Definition Classes
- Params
- final def extractParamMap(): ParamMap
extractParamMap
with no extra values.extractParamMap
with no extra values.- Definition Classes
- Params
- final def extractParamMap(extra: ParamMap): ParamMap
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 less than user-supplied values less than 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 less than user-supplied values less than extra.
- Definition Classes
- Params
- def findSynonyms(vec: Vector, num: Int): DataFrame
Find "num" number of words whose vector representation is most similar to the supplied vector.
Find "num" number of words whose vector representation is most similar to the supplied vector. If the supplied vector is the vector representation of a word in the model's vocabulary, that word will be in the results.
- returns
a dataframe with columns "word" and "similarity" of the word and the cosine similarities between the synonyms and the given word vector.
- Annotations
- @Since("2.0.0")
- def findSynonyms(word: String, num: Int): DataFrame
Find "num" number of words closest in similarity to the given word, not including the word itself.
Find "num" number of words closest in similarity to the given word, not including the word itself.
- returns
a dataframe with columns "word" and "similarity" of the word and the cosine similarities between the synonyms and the given word.
- Annotations
- @Since("1.5.0")
- def findSynonymsArray(word: String, num: Int): Array[(String, Double)]
Find "num" number of words closest in similarity to the given word, not including the word itself.
Find "num" number of words closest in similarity to the given word, not including the word itself.
- returns
an array of the words and the cosine similarities between the synonyms given word vector.
- Annotations
- @Since("2.2.0")
- def findSynonymsArray(vec: Vector, num: Int): Array[(String, Double)]
Find "num" number of words whose vector representation is most similar to the supplied vector.
Find "num" number of words whose vector representation is most similar to the supplied vector. If the supplied vector is the vector representation of a word in the model's vocabulary, that word will be in the results.
- returns
an array of the words and the cosine similarities between the synonyms given word vector.
- Annotations
- @Since("2.2.0")
- final def get[T](param: Param[T]): Option[T]
Optionally returns the user-supplied value of a param.
Optionally returns the user-supplied value of a param.
- Definition Classes
- Params
- final def getDefault[T](param: Param[T]): Option[T]
Gets the default value of a parameter.
Gets the default value of a parameter.
- Definition Classes
- Params
- final def getOrDefault[T](param: Param[T]): T
Gets the value of a param in the embedded param map or its default value.
Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.
- Definition Classes
- Params
- def getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
- Definition Classes
- Params
- lazy val getVectors: DataFrame
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 a dataframe with two fields, "word" and "vector", with "word" being a String and and the vector the DenseVector that it is mapped to.
- Annotations
- @Since("1.5.0") @transient()
- final def hasDefault[T](param: Param[T]): Boolean
Tests whether the input param has a default value set.
Tests whether the input param has a default value set.
- Definition Classes
- Params
- def hasParam(paramName: String): Boolean
Tests whether this instance contains a param with a given name.
Tests whether this instance contains a param with a given name.
- Definition Classes
- Params
- def hasParent: Boolean
Indicates whether this Model has a corresponding parent.
- final def isDefined(param: Param[_]): Boolean
Checks whether a param is explicitly set or has a default value.
Checks whether a param is explicitly set or has a default value.
- Definition Classes
- Params
- final def isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
- Definition Classes
- Params
- lazy val params: Array[Param[_]]
Returns all params sorted by their names.
Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.
- Definition Classes
- Params
- Note
Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.
- var parent: Estimator[Word2VecModel]
The parent estimator that produced this model.
The parent estimator that produced this model.
- Definition Classes
- Model
- Note
For ensembles' component Models, this value can be null.
- def save(path: String): Unit
Saves this ML instance to the input path, a shortcut of
write.save(path)
.Saves this ML instance to the input path, a shortcut of
write.save(path)
.- Definition Classes
- MLWritable
- Annotations
- @Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")
- final def set[T](param: Param[T], value: T): Word2VecModel.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
- Definition Classes
- Params
- def setParent(parent: Estimator[Word2VecModel]): Word2VecModel
Sets the parent of this model (Java API).
Sets the parent of this model (Java API).
- Definition Classes
- Model
- def toString(): String
- Definition Classes
- Word2VecModel → Identifiable → AnyRef → Any
- Annotations
- @Since("3.0.0")
- def transform(dataset: Dataset[_]): DataFrame
Transform a sentence column to a vector column to represent the whole sentence.
Transform a sentence column to a vector column to represent the whole sentence. The transform is performed by averaging all word vectors it contains.
- Definition Classes
- Word2VecModel → Transformer
- Annotations
- @Since("2.0.0")
- def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
Transforms the dataset with provided parameter map as additional parameters.
Transforms the dataset with provided parameter map as additional parameters.
- dataset
input dataset
- paramMap
additional parameters, overwrite embedded params
- returns
transformed dataset
- Definition Classes
- Transformer
- Annotations
- @Since("2.0.0")
- def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
Transforms the dataset with optional parameters
Transforms the dataset with optional parameters
- dataset
input dataset
- firstParamPair
the first param pair, overwrite embedded params
- otherParamPairs
other param pairs, overwrite embedded params
- returns
transformed dataset
- Definition Classes
- Transformer
- Annotations
- @Since("2.0.0") @varargs()
- def transformSchema(schema: StructType): StructType
Check transform validity and derive the output schema from the input schema.
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 byParam.validate()
.Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Definition Classes
- Word2VecModel → PipelineStage
- Annotations
- @Since("1.4.0")
- val uid: String
An immutable unique ID for the object and its derivatives.
An immutable unique ID for the object and its derivatives.
- Definition Classes
- Word2VecModel → Identifiable
- Annotations
- @Since("1.4.0")
- def write: MLWriter
Returns an
MLWriter
instance for this ML instance.Returns an
MLWriter
instance for this ML instance.- Definition Classes
- Word2VecModel → MLWritable
- Annotations
- @Since("1.6.0")
Parameter setters
- def setInputCol(value: String): Word2VecModel.this.type
- Annotations
- @Since("1.4.0")
- def setOutputCol(value: String): Word2VecModel.this.type
- Annotations
- @Since("1.4.0")
Parameter getters
- final def getInputCol: String
- Definition Classes
- HasInputCol
- final def getMaxIter: Int
- Definition Classes
- HasMaxIter
- def getMaxSentenceLength: Int
- Definition Classes
- Word2VecBase
- def getMinCount: Int
- Definition Classes
- Word2VecBase
- def getNumPartitions: Int
- Definition Classes
- Word2VecBase
- final def getOutputCol: String
- Definition Classes
- HasOutputCol
- final def getSeed: Long
- Definition Classes
- HasSeed
- final def getStepSize: Double
- Definition Classes
- HasStepSize
- def getVectorSize: Int
- Definition Classes
- Word2VecBase
(expert-only) Parameters
A list of advanced, expert-only (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.
(expert-only) Parameter getters
- def getWindowSize: Int
- Definition Classes
- Word2VecBase