public static final class Word2VecV3.Word2VecParametersV3 extends water.api.ModelParametersSchema<Word2VecModel.Word2VecParameters,Word2VecV3.Word2VecParametersV3>
Modifier and Type | Field and Description |
---|---|
int |
epochs |
float |
initLearningRate |
int |
minWordFreq |
int |
negSampleCnt |
Word2Vec.NormModel |
normModel |
static java.lang.String[] |
own_fields |
float |
sentSampleRate |
int |
vecSize |
int |
windowSize |
Word2Vec.WordModel |
wordModel |
Constructor and Description |
---|
Word2VecV3.Word2VecParametersV3() |
append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSON
acceptsFrame, createAndFillImpl, createImpl, extractVersion, fillFromParms, getExperimentalVersion, getHighestSupportedVersion, getImplClass, getImplClass, getLatestVersion, getSchemaVersion, markdown, markdown, markdown, markdown, newInstance, register, registerAllSchemasIfNecessary, schema, schema, schema, schema, schema, schemaClass, schemaClass, schemaClass, schemaClass, schemas
public static java.lang.String[] own_fields
@API(help="Set size of word vectors", required=true) public int vecSize
@API(help="Set max skip length between words", required=true) public int windowSize
@API(help="Set threshold for occurrence of words. Those that appear with higher frequency in the training data\n\t\twill be randomly down-sampled; useful range is (0, 1e-5)", required=true) public float sentSampleRate
@API(help="Use Hierarchical Softmax or Negative Sampling", values={"HSM","NegSampling"}, required=true) public Word2Vec.NormModel normModel
@API(help="Number of negative examples, common values are 3 - 10 (0 = not used)", required=true) public int negSampleCnt
@API(help="Number of training iterations to run", required=true) public int epochs
@API(help="This will discard words that appear less thantimes", required=true) public int minWordFreq
@API(help="Set the starting learning rate", required=true) public float initLearningRate
@API(help="Use the continuous bag of words model or the Skip-Gram model", values={"CBOW","SkipGram"}, required=true) public Word2Vec.WordModel wordModel