org.apache.spark.ml.feature

Class CountVectorizerModel

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, Logging, CountVectorizerParams, Params, HasInputCol, HasOutputCol, Identifiable, MLWritable

public class CountVectorizerModel
extends Model<CountVectorizerModel>
implements CountVectorizerParams, MLWritable

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(String[] vocabulary)
CountVectorizerModel(String uid, String[] vocabulary)

Method Summary

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

CountVectorizerModel

public CountVectorizerModel(String uid,
                            String[] vocabulary)

CountVectorizerModel

public CountVectorizerModel(String[] vocabulary)

Method Detail

read

public static MLReader<CountVectorizerModel> read()

load

public static CountVectorizerModel load(String path)

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)

vocabulary

public String[] vocabulary()

setInputCol

public CountVectorizerModel setInputCol(String value)

setOutputCol

public CountVectorizerModel setOutputCol(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 ::

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 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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Model<CountVectorizerModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

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)