org.apache.spark.ml.tuning

Class CrossValidatorModel

java.lang.Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.tuning.CrossValidatorModel

All Implemented Interfaces:

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

public class CrossValidatorModel
extends Model<CrossValidatorModel>
implements MLWritable

:: Experimental :: Model from k-fold cross validation.

param: bestModel The best model selected from k-fold cross validation. param: avgMetrics Average cross-validation metrics for each paramMap in CrossValidator.estimatorParamMaps, in the corresponding order.

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
double[]	avgMetrics()
java.lang.Object	bestModel()
CrossValidatorModel	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
Estimator<?>	getEstimator()
ParamMap[]	getEstimatorParamMaps()
Evaluator	getEvaluator()
int	getNumFolds()
static CrossValidatorModel	load(java.lang.String path)
IntParam	numFolds() Param for number of folds for cross validation.
static MLReader<CrossValidatorModel>	read()
DataFrame	transform(DataFrame dataset) Transforms the input dataset.
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.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

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

Method Detail

read

public static MLReader<CrossValidatorModel> read()

load

public static CrossValidatorModel 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)

bestModel

public java.lang.Object bestModel()

avgMetrics

public double[] avgMetrics()

validateParams

public void validateParams()

Specified by:

validateParams in interface Params

transform

public DataFrame transform(DataFrame 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 CrossValidatorModel 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<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()