org.apache.spark.ml.feature

Class CountVectorizer

Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.feature.CountVectorizer

All Implemented Interfaces:

java.io.Serializable, Logging, CountVectorizerParams, Params, HasInputCol, HasOutputCol, DefaultParamsWritable, Identifiable, MLWritable

public class CountVectorizer
extends Estimator<CountVectorizerModel>
implements CountVectorizerParams, DefaultParamsWritable

Extracts a vocabulary from document collections and generates a CountVectorizerModel.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
CountVectorizer()
CountVectorizer(String uid)

Method Summary

Modifier and Type	Method and Description
CountVectorizer	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
CountVectorizerModel	fit(Dataset<?> dataset) Fits a model to the input data.
static CountVectorizer	load(String path)
static MLReader<T>	read()
CountVectorizer	setBinary(boolean value)
CountVectorizer	setInputCol(String value)
CountVectorizer	setMaxDF(double value)
CountVectorizer	setMinDF(double value)
CountVectorizer	setMinTF(double value)
CountVectorizer	setOutputCol(String value)
CountVectorizer	setVocabSize(int value)
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.

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

fit, fit, fit, fit

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.ml.feature.CountVectorizerParams

binary, getBinary, getMaxDF, getMinDF, getMinTF, getVocabSize, maxDF, minDF, minTF, validateAndTransformSchema, vocabSize

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

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

toString

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

write

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

save

Methods inherited from interface org.apache.spark.internal.Logging

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

CountVectorizer

public CountVectorizer(String uid)

CountVectorizer

public CountVectorizer()

Method Detail

load

public static CountVectorizer load(String path)

read

public static MLReader<T> read()

uid

public 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)

setInputCol

public CountVectorizer setInputCol(String value)

setOutputCol

public CountVectorizer setOutputCol(String value)

setVocabSize

public CountVectorizer setVocabSize(int value)

setMinDF

public CountVectorizer setMinDF(double value)

setMaxDF

public CountVectorizer setMaxDF(double value)

setMinTF

public CountVectorizer setMinTF(double value)

setBinary

public CountVectorizer setBinary(boolean value)

fit

public CountVectorizerModel fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<CountVectorizerModel>

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Check transform validity and derive the output schema from the input schema.

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.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public CountVectorizer 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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Estimator<CountVectorizerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)