class Word2VecModel extends Model[Word2VecModel] with Word2VecBase with MLWritable
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- Word2VecBase
- HasSeed
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- implicit class LogStringContext extends AnyRef
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- final def !=(arg0: Any): Boolean
- Definition Classes
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- final def ##: Int
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- final def $[T](param: Param[T]): T
An alias for
getOrDefault().An alias for
getOrDefault().- Attributes
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- final def ==(arg0: Any): Boolean
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- final def asInstanceOf[T0]: T0
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- 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 clone(): AnyRef
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- protected[lang]
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- 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 copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
Copies param values from this instance to another instance for params shared by them.
Copies param values from this instance to another instance for params shared by them.
This handles default Params and explicitly set Params separately. Default Params are copied from and to
defaultParamMap, and explicitly set Params are copied from and toparamMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.- to
the target instance, which should work with the same set of default Params as this source instance
- extra
extra params to be copied to the target's
paramMap- returns
the target instance with param values copied
- Attributes
- protected
- Definition Classes
- Params
- final def defaultCopy[T <: Params](extra: ParamMap): T
Default implementation of copy with extra params.
Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.
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- protected
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- Params
- final def eq(arg0: AnyRef): Boolean
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- def equals(arg0: AnyRef): Boolean
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- AnyRef → Any
- 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
extractParamMapwith no extra values.extractParamMapwith 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 getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- 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 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 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
- final def getOutputCol: String
- Definition Classes
- HasOutputCol
- def getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
- Definition Classes
- Params
- final def getSeed: Long
- Definition Classes
- HasSeed
- final def getStepSize: Double
- Definition Classes
- HasStepSize
- def getVectorSize: Int
- Definition Classes
- Word2VecBase
- 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()
- def getWindowSize: Int
- Definition Classes
- Word2VecBase
- 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.
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
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- protected
- Definition Classes
- Logging
- final val inputCol: Param[String]
Param for input column name.
Param for input column name.
- Definition Classes
- HasInputCol
- 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 isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
- Definition Classes
- Params
- def isTraceEnabled(): Boolean
- Attributes
- protected
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- Logging
- def log: Logger
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- def logDebug(msg: => String, throwable: Throwable): Unit
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- def logDebug(entry: LogEntry, throwable: Throwable): Unit
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- def logDebug(entry: LogEntry): Unit
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- def logDebug(msg: => String): Unit
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- def logError(msg: => String, throwable: Throwable): Unit
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- def logError(entry: LogEntry, throwable: Throwable): Unit
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- def logError(entry: LogEntry): Unit
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- def logError(msg: => String): Unit
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- def logInfo(msg: => String, throwable: Throwable): Unit
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- def logInfo(entry: LogEntry, throwable: Throwable): Unit
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- def logInfo(entry: LogEntry): Unit
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- def logInfo(msg: => String): Unit
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- def logName: String
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- def logTrace(msg: => String, throwable: Throwable): Unit
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- def logTrace(entry: LogEntry, throwable: Throwable): Unit
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- def logTrace(entry: LogEntry): Unit
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- def logTrace(msg: => String): Unit
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- def logWarning(msg: => String, throwable: Throwable): Unit
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- def logWarning(entry: LogEntry, throwable: Throwable): Unit
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- def logWarning(entry: LogEntry): Unit
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- Definition Classes
- Logging
- def logWarning(msg: => String): Unit
- Attributes
- protected
- Definition Classes
- Logging
- 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
maxSentenceLengthsize. 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 def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
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- @IntrinsicCandidate() @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- 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
- 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 val seed: LongParam
Param for random seed.
Param for random seed.
- Definition Classes
- HasSeed
- final def set(paramPair: ParamPair[_]): Word2VecModel.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
- Attributes
- protected
- Definition Classes
- Params
- final def set(param: String, value: Any): Word2VecModel.this.type
Sets a parameter (by name) in the embedded param map.
Sets a parameter (by name) in the embedded param map.
- Attributes
- protected
- Definition Classes
- Params
- 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
- final def setDefault(paramPairs: ParamPair[_]*): Word2VecModel.this.type
Sets default values for a list of params.
Sets default values for a list of params.
Note: Java developers should use the single-parameter
setDefault. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.- paramPairs
a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.
- Attributes
- protected
- Definition Classes
- Params
- final def setDefault[T](param: Param[T], value: T): Word2VecModel.this.type
Sets a default value for a param.
- def setInputCol(value: String): Word2VecModel.this.type
- Annotations
- @Since("1.4.0")
- def setOutputCol(value: String): Word2VecModel.this.type
- Annotations
- @Since("1.4.0")
- 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
- 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 def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- 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
transformSchemaand 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")
- def transformSchema(schema: StructType, logging: Boolean): StructType
:: DeveloperApi ::
:: DeveloperApi ::
Derives the output schema from the input schema and parameters, optionally with logging.
This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
- 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 validateAndTransformSchema(schema: StructType): StructType
Validate and transform the input schema.
Validate and transform the input schema.
- Attributes
- protected
- Definition Classes
- Word2VecBase
- 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
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final val windowSize: IntParam
The window size (context words from [-window, window]).
The window size (context words from [-window, window]). Default: 5
- Definition Classes
- Word2VecBase
- def withLogContext(context: HashMap[String, String])(body: => Unit): Unit
- Attributes
- protected
- Definition Classes
- Logging
- def write: MLWriter
Returns an
MLWriterinstance for this ML instance.Returns an
MLWriterinstance for this ML instance.- Definition Classes
- Word2VecModel → MLWritable
- Annotations
- @Since("1.6.0")
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)
Inherited from MLWritable
Inherited from Word2VecBase
Inherited from HasSeed
Inherited from HasStepSize
Inherited from HasMaxIter
Inherited from HasOutputCol
Inherited from HasInputCol
Inherited from Model[Word2VecModel]
Inherited from Transformer
Inherited from PipelineStage
Inherited from Logging
Inherited from Params
Inherited from Serializable
Inherited from Identifiable
Inherited from AnyRef
Inherited from Any
Parameters
A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.
Members
Parameter setters
Parameter getters
(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.