org.apache.spark.ml.tuning

Class CrossValidatorModel

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, org.apache.spark.internal.Logging, Params, HasSeed, CrossValidatorParams, ValidatorParams, Identifiable, MLWritable

public class CrossValidatorModel
extends Model<CrossValidatorModel>
implements CrossValidatorParams, MLWritable

CrossValidatorModel contains the model with the highest average cross-validation metric across folds and uses this model to transform input data. CrossValidatorModel also tracks the metrics for each param map evaluated.

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

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CrossValidatorModel.CrossValidatorModelWriter Writer for CrossValidatorModel.

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method and Description
double[]	avgMetrics()
Model<?>	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
Param<String>	foldCol() Param for the column name of user specified fold number.
boolean	hasSubModels()
static CrossValidatorModel	load(String path)
IntParam	numFolds() Param for number of folds for cross validation.
static MLReader<CrossValidatorModel>	read()
LongParam	seed() Param for random seed.
Model<?>[][]	subModels()
String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.
String	uid() An immutable unique ID for the object and its derivatives.
CrossValidatorModel.CrossValidatorModelWriter	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

params

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.ml.tuning.CrossValidatorParams

getFoldCol, getNumFolds

Methods inherited from interface org.apache.spark.ml.tuning.ValidatorParams

getEstimator, getEstimatorParamMaps, getEvaluator, logTuningParams, transformSchemaImpl

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed

getSeed

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, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

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

save

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

$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Method Detail

read

public static MLReader<CrossValidatorModel> read()

load

public static CrossValidatorModel load(String path)

numFolds

public IntParam numFolds()

Description copied from interface: CrossValidatorParams

Param for number of folds for cross validation. Must be &gt;= 2. Default: 3

Specified by:

numFolds in interface CrossValidatorParams

Returns:

(undocumented)

foldCol

public Param<String> foldCol()

Description copied from interface: CrossValidatorParams

Param for the column name of user specified fold number. Once this is specified, CrossValidator won't do random k-fold split. Note that this column should be integer type with range [0, numFolds) and Spark will throw exception on out-of-range fold numbers.

Specified by:

foldCol in interface CrossValidatorParams

Returns:

(undocumented)

estimator

public Param<Estimator<?>> estimator()

Description copied from interface: ValidatorParams

param for the estimator to be validated

Specified by:

estimator in interface ValidatorParams

Returns:

(undocumented)

estimatorParamMaps

public Param<ParamMap[]> estimatorParamMaps()

Description copied from interface: ValidatorParams

param for estimator param maps

Specified by:

estimatorParamMaps in interface ValidatorParams

Returns:

(undocumented)

evaluator

public Param<Evaluator> evaluator()

Description copied from interface: ValidatorParams

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

Specified by:

evaluator in interface ValidatorParams

Returns:

(undocumented)

seed

public final LongParam seed()

Description copied from interface: HasSeed

Param for random seed.

Specified by:

seed in interface HasSeed

Returns:

(undocumented)

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)

bestModel

public Model<?> bestModel()

avgMetrics

public double[] avgMetrics()

subModels

public Model<?>[][] subModels()

Returns:

submodels represented in two dimension array. The index of outer array is the fold index, and the index of inner array corresponds to the ordering of estimatorParamMaps

Throws:

IllegalArgumentException - if subModels are not available. To retrieve subModels, make sure to set collectSubModels to true before fitting.

hasSubModels

public boolean hasSubModels()

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

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 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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Model<CrossValidatorModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

write

public CrossValidatorModel.CrossValidatorModelWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object