org.apache.spark.ml.feature

Interface CountVectorizerParams

All Superinterfaces:

HasInputCol, HasOutputCol, Identifiable, Params, java.io.Serializable

All Known Implementing Classes:

CountVectorizer, CountVectorizerModel

public interface CountVectorizerParams
extends Params, HasInputCol, HasOutputCol

Params for CountVectorizer and CountVectorizerModel.

Method Summary

Modifier and Type	Method and Description
BooleanParam	binary() Binary toggle to control the output vector values.
boolean	getBinary()
double	getMaxDF()
double	getMinDF()
double	getMinTF()
int	getVocabSize()
DoubleParam	maxDF() Specifies the maximum number of different documents a term could appear in to be included in the vocabulary.
DoubleParam	minDF() Specifies the minimum number of different documents a term must appear in to be included in the vocabulary.
DoubleParam	minTF() Filter to ignore rare words in a document.
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.
IntParam	vocabSize() Max size of the vocabulary.

Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol

getInputCol, inputCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol

getOutputCol, outputCol

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Method Detail

binary

BooleanParam binary()

Binary toggle to control the output vector values. If True, all nonzero counts (after minTF filter applied) are set to 1. This is useful for discrete probabilistic models that model binary events rather than integer counts. Default: false

Returns:

(undocumented)

getBinary

boolean getBinary()

getMaxDF

double getMaxDF()

getMinDF

double getMinDF()

getMinTF

double getMinTF()

getVocabSize

int getVocabSize()

maxDF

DoubleParam maxDF()

Specifies the maximum number of different documents a term could appear in to be included in the vocabulary. A term that appears more than the threshold will be ignored. If this is an integer greater than or equal to 1, this specifies the maximum number of documents the term could appear in; if this is a double in [0,1), then this specifies the maximum fraction of documents the term could appear in.

Default: (2^63^) - 1

Returns:

(undocumented)

minDF

DoubleParam minDF()

Specifies the minimum number of different documents a term must appear in to be included in the vocabulary. If this is an integer greater than or equal to 1, this specifies the number of documents the term must appear in; if this is a double in [0,1), then this specifies the fraction of documents.

Default: 1.0

Returns:

(undocumented)

minTF

DoubleParam minTF()

Filter to ignore rare words in a document. For each document, terms with frequency/count less than the given threshold are ignored. If this is an integer greater than or equal to 1, then this specifies a count (of times the term must appear in the document); if this is a double in [0,1), then this specifies a fraction (out of the document's token count).

Note that the parameter is only used in transform of CountVectorizerModel and does not affect fitting.

Default: 1.0

Returns:

(undocumented)

validateAndTransformSchema

StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.

vocabSize

IntParam vocabSize()

Max size of the vocabulary. CountVectorizer will build a vocabulary that only considers the top vocabSize terms ordered by term frequency across the corpus.

Default: 2^18^

Returns:

(undocumented)