org.apache.spark.ml.feature

Class CountVectorizerModel

java.lang.Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<CountVectorizerModel>

org.apache.spark.ml.feature.CountVectorizerModel

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable, MLWritable

public class CountVectorizerModel
extends Model<CountVectorizerModel>
implements MLWritable

:: Experimental :: Converts a text document to a sparse vector of token counts. param: vocabulary An Array over terms. Only the terms in the vocabulary will be counted.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
CountVectorizerModel(java.lang.String[] vocabulary)
CountVectorizerModel(java.lang.String uid, java.lang.String[] vocabulary)

Method Summary

Methods

Modifier and Type	Method and Description
protected static <T> T	$(Param<T> param)
static BooleanParam	binary()
BooleanParam	binary() Binary toggle to control the output vector values.
static Params	clear(Param<?> param)
CountVectorizerModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
protected static <T extends Params> T	copyValues(T to, ParamMap extra)
protected static <T extends Params> ParamMap	copyValues$default$2()
protected static <T extends Params> T	defaultCopy(ParamMap extra)
static java.lang.String	explainParam(Param<?> param)
static java.lang.String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static <T> scala.Option<T>	get(Param<T> param)
static boolean	getBinary()
boolean	getBinary()
static <T> scala.Option<T>	getDefault(Param<T> param)
static java.lang.String	getInputCol()
static double	getMinDF()
double	getMinDF()
static double	getMinTF()
double	getMinTF()
static <T> T	getOrDefault(Param<T> param)
static java.lang.String	getOutputCol()
static Param<java.lang.Object>	getParam(java.lang.String paramName)
static int	getVocabSize()
int	getVocabSize()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(java.lang.String paramName)
static boolean	hasParent()
protected static void	initializeLogIfNecessary(boolean isInterpreter)
static Param<java.lang.String>	inputCol()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
protected static boolean	isTraceEnabled()
static CountVectorizerModel	load(java.lang.String path)
protected static org.slf4j.Logger	log()
protected static void	logDebug(scala.Function0<java.lang.String> msg)
protected static void	logDebug(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void	logError(scala.Function0<java.lang.String> msg)
protected static void	logError(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void	logInfo(scala.Function0<java.lang.String> msg)
protected static void	logInfo(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static java.lang.String	logName()
protected static void	logTrace(scala.Function0<java.lang.String> msg)
protected static void	logTrace(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void	logWarning(scala.Function0<java.lang.String> msg)
protected static void	logWarning(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
static DoubleParam	minDF()
DoubleParam	minDF() Specifies the minimum number of different documents a term must appear in to be included in the vocabulary.
static DoubleParam	minTF()
DoubleParam	minTF() Filter to ignore rare words in a document.
static Param<java.lang.String>	outputCol()
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static MLReader<CountVectorizerModel>	read()
static void	save(java.lang.String path)
static <T> Params	set(Param<T> param, T value)
protected static Params	set(ParamPair<?> paramPair)
protected static Params	set(java.lang.String param, java.lang.Object value)
CountVectorizerModel	setBinary(boolean value)
protected static <T> Params	setDefault(Param<T> param, T value)
protected static Params	setDefault(scala.collection.Seq<ParamPair<?>> paramPairs)
CountVectorizerModel	setInputCol(java.lang.String value)
CountVectorizerModel	setMinTF(double value)
CountVectorizerModel	setOutputCol(java.lang.String value)
static M	setParent(Estimator<M> parent)
static java.lang.String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
protected static StructType	validateAndTransformSchema(StructType schema)
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.
static void	validateParams()
static IntParam	vocabSize()
IntParam	vocabSize() Max size of the vocabulary.
java.lang.String[]	vocabulary()
MLWriter	write() Returns an MLWriter instance for this ML instance.

Methods inherited from class org.apache.spark.ml.Model

hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer

transform, transform, transform

Methods inherited from class org.apache.spark.ml.PipelineStage

transformSchema

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

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

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

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

toString

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

save

Constructor Detail

CountVectorizerModel

public CountVectorizerModel(java.lang.String uid,
                    java.lang.String[] vocabulary)

CountVectorizerModel

public CountVectorizerModel(java.lang.String[] vocabulary)

Method Detail

read

public static MLReader<CountVectorizerModel> read()

load

public static CountVectorizerModel load(java.lang.String path)

toString

public static java.lang.String toString()

params

public static Param<?>[] params()

validateParams

public static void validateParams()

explainParam

public static java.lang.String explainParam(Param<?> param)

explainParams

public static java.lang.String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(java.lang.String paramName)

getParam

public static Param<java.lang.Object> getParam(java.lang.String paramName)

set

public static final <T> Params set(Param<T> param,
             T value)

set

protected static final Params set(java.lang.String param,
         java.lang.Object value)

set

protected static final Params set(ParamPair<?> paramPair)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

$

protected static final <T> T $(Param<T> param)

setDefault

protected static final <T> Params setDefault(Param<T> param,
                    T value)

setDefault

protected static final Params setDefault(scala.collection.Seq<ParamPair<?>> paramPairs)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

defaultCopy

protected static final <T extends Params> T defaultCopy(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

copyValues

protected static <T extends Params> T copyValues(T to,
                              ParamMap extra)

copyValues$default$2

protected static <T extends Params> ParamMap copyValues$default$2()

logName

protected static java.lang.String logName()

log

protected static org.slf4j.Logger log()

logInfo

protected static void logInfo(scala.Function0<java.lang.String> msg)

logDebug

protected static void logDebug(scala.Function0<java.lang.String> msg)

logTrace

protected static void logTrace(scala.Function0<java.lang.String> msg)

logWarning

protected static void logWarning(scala.Function0<java.lang.String> msg)

logError

protected static void logError(scala.Function0<java.lang.String> msg)

logInfo

protected static void logInfo(scala.Function0<java.lang.String> msg,
           java.lang.Throwable throwable)

logDebug

protected static void logDebug(scala.Function0<java.lang.String> msg,
            java.lang.Throwable throwable)

logTrace

protected static void logTrace(scala.Function0<java.lang.String> msg,
            java.lang.Throwable throwable)

logWarning

protected static void logWarning(scala.Function0<java.lang.String> msg,
              java.lang.Throwable throwable)

logError

protected static void logError(scala.Function0<java.lang.String> msg,
            java.lang.Throwable throwable)

isTraceEnabled

protected static boolean isTraceEnabled()

initializeLogIfNecessary

protected static void initializeLogIfNecessary(boolean isInterpreter)

parent

public static Estimator<M> parent()

parent_$eq

public static void parent_$eq(Estimator<M> x$1)

setParent

public static M setParent(Estimator<M> parent)

hasParent

public static boolean hasParent()

inputCol

public static final Param<java.lang.String> inputCol()

getInputCol

public static final java.lang.String getInputCol()

outputCol

public static final Param<java.lang.String> outputCol()

getOutputCol

public static final java.lang.String getOutputCol()

vocabSize

public static IntParam vocabSize()

getVocabSize

public static int getVocabSize()

minDF

public static DoubleParam minDF()

getMinDF

public static double getMinDF()

validateAndTransformSchema

protected static StructType validateAndTransformSchema(StructType schema)

minTF

public static DoubleParam minTF()

getMinTF

public static double getMinTF()

binary

public static BooleanParam binary()

getBinary

public static boolean getBinary()

save

public static void save(java.lang.String path)
                 throws java.io.IOException

Throws:

java.io.IOException

uid

public java.lang.String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

vocabulary

public java.lang.String[] vocabulary()

setInputCol

public CountVectorizerModel setInputCol(java.lang.String value)

setOutputCol

public CountVectorizerModel setOutputCol(java.lang.String value)

setMinTF

public CountVectorizerModel setMinTF(double value)

setBinary

public CountVectorizerModel setBinary(boolean value)

transform

public Dataset<Row> transform(Dataset<?> dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Derives the output schema from the input schema.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public CountVectorizerModel copy(ParamMap extra)

Description copied from interface: 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.

Specified by:

copy in interface Params

Specified by:

copy in class Model<CountVectorizerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

vocabSize

public 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)

getVocabSize

public int getVocabSize()

minDF

public 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 >= 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

Returns:

(undocumented)

getMinDF

public double getMinDF()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.

minTF

public 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 >= 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

Returns:

(undocumented)

getMinTF

public double getMinTF()

binary

public 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

public boolean getBinary()