org.apache.spark.ml.tuning

Class TrainValidationSplit

java.lang.Object

org.apache.spark.ml.PipelineStage

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

org.apache.spark.ml.tuning.TrainValidationSplit

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable

public class TrainValidationSplit
extends Estimator<TrainValidationSplitModel>
implements Logging

:: Experimental :: Validation for hyper-parameter tuning. Randomly splits the input dataset into train and validation sets, and uses evaluation metric on the validation set to select the best model. Similar to CrossValidator, but only splits the set once.

See Also:

Serialized Form

Constructor Summary

Constructors

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

Method Summary

Methods

Modifier and Type	Method and Description
TrainValidationSplit	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
TrainValidationSplitModel	fit(DataFrame dataset) Fits a model to the input data.
Estimator<?>	getEstimator()
ParamMap[]	getEstimatorParamMaps()
Evaluator	getEvaluator()
double	getTrainRatio()
TrainValidationSplit	setEstimator(Estimator<?> value)
TrainValidationSplit	setEstimatorParamMaps(ParamMap[] value)
TrainValidationSplit	setEvaluator(Evaluator value)
TrainValidationSplit	setTrainRatio(double value)
DoubleParam	trainRatio() Param for ratio between train and validation data.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
void	validateParams() Validates parameter values stored internally.

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.Logging

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

Constructor Detail

TrainValidationSplit

public TrainValidationSplit(java.lang.String uid)

TrainValidationSplit

public TrainValidationSplit()

Method Detail

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 TrainValidationSplit setEstimator(Estimator<?> value)

setEstimatorParamMaps

public TrainValidationSplit setEstimatorParamMaps(ParamMap[] value)

setEvaluator

public TrainValidationSplit setEvaluator(Evaluator value)

setTrainRatio

public TrainValidationSplit setTrainRatio(double value)

fit

public TrainValidationSplitModel fit(DataFrame dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<TrainValidationSplitModel>

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()

Description copied from interface: Params

Validates parameter values stored internally. Raise an exception if any parameter value is invalid.

This only needs to check for interactions between parameters. Parameter value checks which do not depend on other parameters are handled by Param.validate(). This method does not handle input/output column parameters; those are checked during schema validation.

Specified by:

validateParams in interface Params

copy

public TrainValidationSplit 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<TrainValidationSplitModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

trainRatio

public DoubleParam trainRatio()

Param for ratio between train and validation data. Must be between 0 and 1. Default: 0.75

Returns:

(undocumented)

getTrainRatio

public double getTrainRatio()

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()