public class Word2Vec extends hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
Modifier and Type | Class and Description |
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static class |
Word2Vec.NormModel |
static class |
Word2Vec.WordModel |
Constructor and Description |
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Word2Vec(boolean startup_once) |
Word2Vec(Word2VecModel.Word2VecParameters parms) |
Modifier and Type | Method and Description |
---|---|
hex.ModelBuilder.BuilderVisibility |
builderVisibility() |
hex.ModelCategory[] |
can_build() |
boolean |
haveMojo() |
protected void |
ignoreBadColumns(int npredictors,
boolean expensive) |
void |
init(boolean expensive)
Initialize the ModelBuilder, validating all arguments and preparing the
training frame.
|
boolean |
isSupervised() |
protected hex.word2vec.Word2Vec.Word2VecDriver |
trainModelImpl() |
algoName, algos, checkDistributions, checkMemoryFootPrint, clearInitState, clearValidationErrors, computeCrossValidation, computePriorClassDistribution, cv_AssignFold, cv_buildModels, cv_computeAndSetOptimalParameters, cv_mainModelScores, cv_makeFramesAndBuilders, cv_makeWeights, cv_scoreCVModels, defaultKey, desiredChunks, dest, error_count, error, get, getToEigenVec, hasFoldCol, hasOffsetCol, hasWeightCol, havePojo, hide, ignoreConstColumns, ignoreInvalidColumns, ignoreStringColumns, info, init_adaptFrameToTrain, isClassifier, isStopped, javaName, logMe, make, message, nclasses, nFoldCV, nFoldWork, nModelsInParallel, numSpecialCols, paramName, rebalance, response, schemaDirectory, separateFeatureVecs, setTrain, shouldReorder, specialColNames, stop_requested, timeout, train, trainModel, trainModelNested, valid, validationErrors, vresponse, warn
public Word2Vec(boolean startup_once)
public Word2Vec(Word2VecModel.Word2VecParameters parms)
public hex.ModelCategory[] can_build()
can_build
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
public hex.ModelBuilder.BuilderVisibility builderVisibility()
builderVisibility
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
public boolean isSupervised()
isSupervised
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
protected hex.word2vec.Word2Vec.Word2VecDriver trainModelImpl()
trainModelImpl
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
public void init(boolean expensive)
init
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
protected void ignoreBadColumns(int npredictors, boolean expensive)
ignoreBadColumns
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>
public boolean haveMojo()
haveMojo
in class hex.ModelBuilder<Word2VecModel,Word2VecModel.Word2VecParameters,Word2VecModel.Word2VecOutput>