Package weka.classifiers

Class BinnedNumericClassCrossValidationFoldGenerator

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.core.option.AbstractOptionHandler

weka.classifiers.AbstractSplitGenerator

weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

All Implemented Interfaces:

Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, Randomizable, SizeOfHandler, BinningAlgorithmUser, CrossValidationFoldGenerator<weka.core.Instances,WekaTrainTestSetContainer>, PerFoldCrossValidationFoldGenerator<weka.core.Instances,WekaTrainTestSetContainer>, SplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>, StratifiableSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>, InstancesViewSupporter, Serializable, Iterator<WekaTrainTestSetContainer>, CrossValidationFoldGenerator, PerFoldCrossValidationFoldGenerator, SplitGenerator

public class BinnedNumericClassCrossValidationFoldGenerator
extends AbstractSplitGenerator
implements CrossValidationFoldGenerator, BinningAlgorithmUser, PerFoldCrossValidationFoldGenerator

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 BinningAlgorithm	m_Algorithm	the binning algorithm.
protected int	m_CurrentFold	the current fold.
protected List<FoldPair<Binnable<weka.core.Instance>>>	m_FoldPairs	the temporary pairs.
protected int	m_NumFolds	the number of folds.
protected boolean	m_Randomize	whether to randomize the data.
protected String	m_RelationName	the template for the relation name.
protected boolean	m_Stratify	whether to stratify the data (in case of nominal class).

Fields inherited from class weka.classifiers.AbstractSplitGenerator

m_Data, m_Initialized, m_OriginalIndices, m_OriginalIndicesPerFold, 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
BinnedNumericClassCrossValidationFoldGenerator()	Initializes the generator.
BinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data, BinningAlgorithm algorithm, int numFolds, long seed, boolean stratify)	Initializes the generator.
BinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data, BinningAlgorithm algorithm, int numFolds, long seed, boolean randomize, boolean stratify, String relName)	Initializes the generator.

Method Summary

Modifier and Type	Method	Description
String	algorithmTipText()	Returns the tip text for this property.
protected boolean	canRandomize()	Returns whether randomization is enabled.
protected boolean	checkNext()	Returns true if the iteration has more elements.
protected WekaTrainTestSetContainer	createNext()	Returns the next element in the iteration.
int[]	crossValidationIndices()	Returns the cross-validation indices.
int[][]	crossValidationIndicesPerFold()	Returns the cross-validation indices per fold.
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).
BinningAlgorithm	getAlgorithm()	Returns the binning algorithm.
int	getNumFolds()	Returns the number of folds.
boolean	getRandomize()	Returns whether to randomize the data.
String	getRelationName()	Returns the relation name template.
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.
String	relationNameTipText()	Returns the tip text for this property.
protected void	reset()	Resets the generator.
void	setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.
void	setData(weka.core.Instances 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	setRelationName(String value)	Sets the template for the relation name.
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 weka.classifiers.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 adams.data.weka.InstancesViewSupporter

getUseViews, setUseViews

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 weka.classifiers.SplitGenerator

getData, hasNext, initializeIterator, next, remove

Field Detail

m_NumFolds

protected int m_NumFolds

the 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_RelationName

protected String m_RelationName

the template for the relation name.

m_Randomize

protected boolean m_Randomize

whether to randomize the data.

m_Algorithm

protected BinningAlgorithm m_Algorithm

the binning algorithm.

m_FoldPairs

protected transient List<FoldPair<Binnable<weka.core.Instance>>> m_FoldPairs

the temporary pairs.

Constructor Detail

BinnedNumericClassCrossValidationFoldGenerator

public BinnedNumericClassCrossValidationFoldGenerator()

Initializes the generator.

BinnedNumericClassCrossValidationFoldGenerator

public BinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data,
                                                      BinningAlgorithm algorithm,
                                                      int numFolds,
                                                      long seed,
                                                      boolean stratify)

Initializes the generator.

Parameters:

data - the full dataset

algorithm - the algorithm to use

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

seed - the seed for randomization

stratify - whether to perform stratified CV

BinnedNumericClassCrossValidationFoldGenerator

public BinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data,
                                                      BinningAlgorithm algorithm,
                                                      int numFolds,
                                                      long seed,
                                                      boolean randomize,
                                                      boolean stratify,
                                                      String relName)

Initializes the generator.

Parameters:

data - the full dataset

algorithm - the algorithm to use

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

relName - the relation name template, use null to ignore

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(weka.core.Instances value)

Sets the original data.

Specified by:

setData in interface SplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

setData in interface SplitGenerator

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<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

setNumFolds in interface CrossValidationFoldGenerator

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<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

getNumFolds in interface CrossValidationFoldGenerator

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<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

getActualNumFolds in interface CrossValidationFoldGenerator

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<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

setRandomize in interface CrossValidationFoldGenerator

Parameters:

value - true if to randomize the data

getRandomize

public boolean getRandomize()

Returns whether to randomize the data.

Specified by:

getRandomize in interface CrossValidationFoldGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

getRandomize in interface CrossValidationFoldGenerator

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).

Specified by:

setStratify in interface CrossValidationFoldGenerator

Specified by:

setStratify in interface StratifiableSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Parameters:

value - whether to stratify the data (nominal class)

getStratify

public boolean getStratify()

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

Specified by:

getStratify in interface CrossValidationFoldGenerator

Specified by:

getStratify in interface StratifiableSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

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.

setRelationName

public void setRelationName(String value)

Sets the template for the relation name.

Specified by:

setRelationName in interface CrossValidationFoldGenerator

Parameters:

value - the template

getRelationName

public String getRelationName()

Returns the relation name template.

Specified by:

getRelationName in interface CrossValidationFoldGenerator

Returns:

the template

relationNameTipText

public String relationNameTipText()

Returns the tip text for this property.

Returns:

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

setAlgorithm

public void setAlgorithm(BinningAlgorithm value)

Sets the binning algorithm.

Specified by:

setAlgorithm in interface BinningAlgorithmUser

Parameters:

value - the algorithm

getAlgorithm

public BinningAlgorithm getAlgorithm()

Returns the binning algorithm.

Specified by:

getAlgorithm in interface BinningAlgorithmUser

Returns:

the algorithm

algorithmTipText

public String algorithmTipText()

Returns the tip text for this property.

Specified by:

algorithmTipText in interface BinningAlgorithmUser

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 WekaTrainTestSetContainer 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<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

crossValidationIndices in interface CrossValidationFoldGenerator

Returns:

the indices

crossValidationIndicesPerFold

public int[][] crossValidationIndicesPerFold()

Returns the cross-validation indices per fold.

Specified by:

crossValidationIndicesPerFold in interface PerFoldCrossValidationFoldGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Returns:

the indices

toString

public String toString()

Returns a short description of the generator.

Specified by:

toString in interface SplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

toString in interface SplitGenerator

Overrides:

toString in class AbstractSplitGenerator

Returns:

a short description