public final class Word2Vec extends Estimator<Word2VecModel> implements Word2VecBase, DefaultParamsWritable
Map(String, Vector), i.e. transforms a word into a code for further
natural language processing or machine learning process.| Modifier and Type | Method and Description |
|---|---|
Word2Vec |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Word2VecModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
Param<String> |
inputCol()
Param for input column name.
|
static Word2Vec |
load(String path) |
IntParam |
maxIter()
Param for maximum number of iterations (>= 0).
|
IntParam |
maxSentenceLength()
Sets the maximum length (in words) of each sentence in the input data.
|
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<T> |
read() |
LongParam |
seed()
Param for random seed.
|
Word2Vec |
setInputCol(String value) |
Word2Vec |
setMaxIter(int value) |
Word2Vec |
setMaxSentenceLength(int value) |
Word2Vec |
setMinCount(int value) |
Word2Vec |
setNumPartitions(int value) |
Word2Vec |
setOutputCol(String value) |
Word2Vec |
setSeed(long value) |
Word2Vec |
setStepSize(double value) |
Word2Vec |
setVectorSize(int value) |
Word2Vec |
setWindowSize(int value) |
DoubleParam |
stepSize()
Param for Step size to be used for each iteration of optimization (> 0).
|
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
IntParam |
vectorSize()
The dimension of the code that you want to transform from words.
|
IntParam |
windowSize()
The window size (context words from [-window, window]).
|
paramsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetMaxSentenceLength, getMinCount, getNumPartitions, getVectorSize, getWindowSize, validateAndTransformSchemagetInputColgetOutputColgetMaxItergetStepSizeclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringwritesave$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitializepublic static Word2Vec load(String path)
public static MLReader<T> read()
public final IntParam vectorSize()
Word2VecBasevectorSize in interface Word2VecBasepublic final IntParam windowSize()
Word2VecBasewindowSize in interface Word2VecBasepublic final IntParam numPartitions()
Word2VecBasenumPartitions in interface Word2VecBasepublic final IntParam minCount()
Word2VecBaseminCount in interface Word2VecBasepublic final IntParam maxSentenceLength()
Word2VecBasemaxSentenceLength size.
Default: 1000maxSentenceLength in interface Word2VecBasepublic final LongParam seed()
HasSeedpublic DoubleParam stepSize()
HasStepSizestepSize in interface HasStepSizepublic final IntParam maxIter()
HasMaxItermaxIter in interface HasMaxIterpublic final Param<String> outputCol()
HasOutputColoutputCol in interface HasOutputColpublic final Param<String> inputCol()
HasInputColinputCol in interface HasInputColpublic String uid()
Identifiableuid in interface Identifiablepublic Word2Vec setInputCol(String value)
public Word2Vec setOutputCol(String value)
public Word2Vec setVectorSize(int value)
public Word2Vec setWindowSize(int value)
public Word2Vec setStepSize(double value)
public Word2Vec setNumPartitions(int value)
public Word2Vec setMaxIter(int value)
public Word2Vec setSeed(long value)
public Word2Vec setMinCount(int value)
public Word2Vec setMaxSentenceLength(int value)
public Word2VecModel fit(Dataset<?> dataset)
Estimatorfit in class Estimator<Word2VecModel>dataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
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 by Param.validate().
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema in class PipelineStageschema - (undocumented)public Word2Vec copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Estimator<Word2VecModel>extra - (undocumented)