Package adams.ml.evaluation

Class DefaultCrossValidationFoldGenerator

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.core.option.AbstractOptionHandler

adams.ml.evaluation.AbstractSplitGenerator

adams.ml.evaluation.DefaultCrossValidationFoldGenerator

All Implemented Interfaces:

Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, Randomizable, SizeOfHandler, CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>, SplitGenerator<Dataset,TrainTestSetContainer>, Serializable, Iterator<TrainTestSetContainer>

public class DefaultCrossValidationFoldGenerator
extends AbstractSplitGenerator
implements CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Helper class for generating cross-validation folds.

The template for the relation name accepts the following placeholders:

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected int	m_ActualNumFolds	the actual number of folds.
protected int	m_CurrentFold	the current fold.
protected List<FoldPair<Binnable<DataRow>>>	m_FoldPairs	the temporary pairs.
protected CrossValidationGenerator	m_Generator	the underlying scheme for generating the folds.
protected int	m_NumFolds	the number of folds.
protected boolean	m_Randomize	whether to randomize the data.
protected boolean	m_Stratify	whether to stratify the data (in case of nominal class).

Fields inherited from class adams.ml.evaluation.AbstractSplitGenerator

m_Data, m_Initialized, m_OriginalIndices, m_Seed, m_UseViews

Fields inherited from class adams.core.option.AbstractOptionHandler

m_OptionManager

Fields inherited from class adams.core.logging.LoggingObject

m_Logger, m_LoggingIsEnabled, m_LoggingLevel

Constructor Summary

Constructors

Constructor	Description
DefaultCrossValidationFoldGenerator()	Initializes the generator.
DefaultCrossValidationFoldGenerator(Dataset data, int numFolds, long seed, boolean stratify)	Initializes the generator.
DefaultCrossValidationFoldGenerator(Dataset data, int numFolds, long seed, boolean randomize, boolean stratify)	Initializes the generator.

Method Summary

Modifier and Type	Method	Description
protected boolean	canRandomize()	Returns whether randomization is enabled.
protected boolean	checkNext()	Returns true if the iteration has more elements.
protected TrainTestSetContainer	createNext()	Returns the next element in the iteration.
int[]	crossValidationIndices()	Returns the cross-validation indices.
void	defineOptions()	Adds options to the internal list of options.
protected void	doInitializeIterator()	Initializes the iterator, randomizes the data if required.
int	getActualNumFolds()	Returns the actual number of folds used (eg when using LOO).
int	getNumFolds()	Returns the number of folds.
boolean	getRandomize()	Returns whether to randomize the data.
boolean	getStratify()	Returns whether to stratify the data (in case of nominal class).
String	globalInfo()	Returns a string describing the object.
String	numFoldsTipText()	Returns the tip text for this property.
String	randomizeTipText()	Returns the tip text for this property.
protected void	reset()	Resets the generator.
void	setData(Dataset value)	Sets the original data.
void	setNumFolds(int value)	Sets the number of folds to use.
void	setRandomize(boolean value)	Sets whether to randomize the data.
void	setStratify(boolean value)	Sets whether to stratify the data (nominal class).
String	stratifyTipText()	Returns the tip text for this property.
String	toString()	Returns a short description of the generator.

Methods inherited from class adams.ml.evaluation.AbstractSplitGenerator

getData, getSeed, getUseViews, hasNext, initialize, initializeIterator, next, randomize, remove, seedTipText, setSeed, setUseViews, useViewsTipText

Methods inherited from class adams.core.option.AbstractOptionHandler

cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, loggingLevelTipText, newOptionManager, setLoggingLevel, toCommandLine

Methods inherited from class adams.core.logging.LoggingObject

configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface adams.core.Destroyable

destroy

Methods inherited from interface java.util.Iterator

forEachRemaining

Methods inherited from interface adams.core.logging.LoggingLevelHandler

getLoggingLevel

Methods inherited from interface adams.core.option.OptionHandler

cleanUpOptions, getOptionManager, toCommandLine

Methods inherited from interface adams.core.Randomizable

getSeed, seedTipText, setSeed

Methods inherited from interface adams.data.splitgenerator.SplitGenerator

getData, hasNext, initializeIterator, next, remove

Field Detail

m_NumFolds

protected int m_NumFolds

the number of folds.

m_ActualNumFolds

protected int m_ActualNumFolds

the actual number of folds.

m_Stratify

protected boolean m_Stratify

whether to stratify the data (in case of nominal class).

m_CurrentFold

protected transient int m_CurrentFold

the current fold.

m_Randomize

protected boolean m_Randomize

whether to randomize the data.

m_Generator

protected transient CrossValidationGenerator m_Generator

the underlying scheme for generating the folds.

m_FoldPairs

protected transient List<FoldPair<Binnable<DataRow>>> m_FoldPairs

the temporary pairs.

Constructor Detail

DefaultCrossValidationFoldGenerator

public DefaultCrossValidationFoldGenerator()

Initializes the generator.

DefaultCrossValidationFoldGenerator

public DefaultCrossValidationFoldGenerator(Dataset data,
                                           int numFolds,
                                           long seed,
                                           boolean stratify)

Initializes the generator.

Parameters:

data - the full dataset

numFolds - the number of folds, leave-one-out if less than 2

seed - the seed for randomization

stratify - whether to perform stratified CV

DefaultCrossValidationFoldGenerator

public DefaultCrossValidationFoldGenerator(Dataset data,
                                           int numFolds,
                                           long seed,
                                           boolean randomize,
                                           boolean stratify)

Initializes the generator.

Parameters:

data - the full dataset

numFolds - the number of folds, leave-one-out if less than 2

seed - the seed value

randomize - whether to randomize the data

stratify - whether to perform stratified CV

Method Detail

globalInfo

public String globalInfo()

Returns a string describing the object.

Specified by:

globalInfo in interface GlobalInfoSupporter

Specified by:

globalInfo in class AbstractOptionHandler

Returns:

a description suitable for displaying in the gui

defineOptions

public void defineOptions()

Adds options to the internal list of options.

Specified by:

defineOptions in interface OptionHandler

Overrides:

defineOptions in class AbstractSplitGenerator

reset

protected void reset()

Resets the generator.

Overrides:

reset in class AbstractSplitGenerator

setData

public void setData(Dataset value)

Sets the original data.

Specified by:

setData in interface SplitGenerator<Dataset,TrainTestSetContainer>

Overrides:

setData in class AbstractSplitGenerator

Parameters:

value - the data

setNumFolds

public void setNumFolds(int value)

Sets the number of folds to use.

Specified by:

setNumFolds in interface CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Parameters:

value - the number of folds, less than 2 for LOO

getNumFolds

public int getNumFolds()

Returns the number of folds.

Specified by:

getNumFolds in interface CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Returns:

the number of folds

numFoldsTipText

public String numFoldsTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

getActualNumFolds

public int getActualNumFolds()

Returns the actual number of folds used (eg when using LOO).

Specified by:

getActualNumFolds in interface CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Returns:

the actual number of folds, -1 if not yet calculated

See Also:

AbstractSplitGenerator.initializeIterator()

setRandomize

public void setRandomize(boolean value)

Sets whether to randomize the data.

Specified by:

setRandomize in interface CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Parameters:

value - true if to randomize the data

getRandomize

public boolean getRandomize()

Returns whether to randomize the data.

Specified by:

getRandomize in interface CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Returns:

true if to randomize the data

randomizeTipText

public String randomizeTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setStratify

public void setStratify(boolean value)

Sets whether to stratify the data (nominal class).

Parameters:

value - whether to stratify the data (nominal class)

getStratify

public boolean getStratify()

Returns whether to stratify the data (in case of nominal class).

Returns:

true if to stratify

stratifyTipText

public String stratifyTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

canRandomize

protected boolean canRandomize()

Returns whether randomization is enabled.

Specified by:

canRandomize in class AbstractSplitGenerator

Returns:

true if to randomize

checkNext

protected boolean checkNext()

Returns true if the iteration has more elements. (In other words, returns true if next would return an element rather than throwing an exception.)

Specified by:

checkNext in class AbstractSplitGenerator

Returns:

true if the iterator has more elements.

doInitializeIterator

protected void doInitializeIterator()

Initializes the iterator, randomizes the data if required.

Specified by:

doInitializeIterator in class AbstractSplitGenerator

See Also:

AbstractSplitGenerator.canRandomize()

createNext

protected TrainTestSetContainer createNext()

Returns the next element in the iteration.

Specified by:

createNext in class AbstractSplitGenerator

Returns:

the next element in the iteration.

Throws:

NoSuchElementException - iteration has no more elements.

crossValidationIndices

public int[] crossValidationIndices()

Returns the cross-validation indices.

Specified by:

crossValidationIndices in interface CrossValidationFoldGenerator<Dataset,TrainTestSetContainer>

Returns:

the indices

toString

public String toString()

Returns a short description of the generator.

Specified by:

toString in interface SplitGenerator<Dataset,TrainTestSetContainer>

Overrides:

toString in class AbstractSplitGenerator

Returns:

a short description