org.apache.spark.ml.tuning

Class CrossValidator

java.lang.Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.tuning.CrossValidator

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable, MLWritable

public class CrossValidator
extends Estimator<CrossValidatorModel>
implements MLWritable, Logging

:: Experimental :: K-fold cross validation.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
CrossValidator()
CrossValidator(java.lang.String uid)

Method Summary

Methods

Modifier and Type	Method and Description
CrossValidator	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
Param<Estimator<?>>	estimator() param for the estimator to be validated
Param<ParamMap[]>	estimatorParamMaps() param for estimator param maps
Param<Evaluator>	evaluator() param for the evaluator used to select hyper-parameters that maximize the validated metric
CrossValidatorModel	fit(DataFrame dataset) Fits a model to the input data.
Estimator<?>	getEstimator()
ParamMap[]	getEstimatorParamMaps()
Evaluator	getEvaluator()
int	getNumFolds()
static CrossValidator	load(java.lang.String path)
IntParam	numFolds() Param for number of folds for cross validation.
static MLReader<CrossValidator>	read()
CrossValidator	setEstimator(Estimator<?> value)
CrossValidator	setEstimatorParamMaps(ParamMap[] value)
CrossValidator	setEvaluator(Evaluator value)
CrossValidator	setNumFolds(int value)
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
void	validateParams()
MLWriter	write() Returns an MLWriter instance for this ML instance.

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

fit, fit, fit, fit

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

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.Logging

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

Constructor Detail

CrossValidator

public CrossValidator(java.lang.String uid)

CrossValidator

public CrossValidator()

Method Detail

read

public static MLReader<CrossValidator> read()

load

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

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)

setEstimator

public CrossValidator setEstimator(Estimator<?> value)

setEstimatorParamMaps

public CrossValidator setEstimatorParamMaps(ParamMap[] value)

setEvaluator

public CrossValidator setEvaluator(Evaluator value)

setNumFolds

public CrossValidator setNumFolds(int value)

fit

public CrossValidatorModel fit(DataFrame dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<CrossValidatorModel>

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)

validateParams

public void validateParams()

Specified by:

validateParams in interface Params

copy

public CrossValidator 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 Estimator<CrossValidatorModel>

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)

numFolds

public IntParam numFolds()

Param for number of folds for cross validation. Must be >= 2. Default: 3

Returns:

(undocumented)

getNumFolds

public int getNumFolds()

estimator

public Param<Estimator<?>> estimator()

param for the estimator to be validated

Returns:

(undocumented)

getEstimator

public Estimator<?> getEstimator()

estimatorParamMaps

public Param<ParamMap[]> estimatorParamMaps()

param for estimator param maps

Returns:

(undocumented)

getEstimatorParamMaps

public ParamMap[] getEstimatorParamMaps()

evaluator

public Param<Evaluator> evaluator()

param for the evaluator used to select hyper-parameters that maximize the validated metric

Returns:

(undocumented)

getEvaluator

public Evaluator getEvaluator()