Package weka.classifiers

Class BestBinnedNumericClassRandomSplitGenerator

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.core.option.AbstractOptionHandler

weka.classifiers.AbstractSplitGenerator

weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

All Implemented Interfaces:

adams.core.Destroyable, adams.core.GlobalInfoSupporter, adams.core.logging.LoggingLevelHandler, adams.core.logging.LoggingSupporter, adams.core.option.OptionHandler, adams.core.Randomizable, adams.core.SizeOfHandler, adams.data.splitgenerator.RandomSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>, adams.data.splitgenerator.SplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>, InstancesViewSupporter, Serializable, Iterator<WekaTrainTestSetContainer>, RandomSplitGenerator, SplitGenerator

public class BestBinnedNumericClassRandomSplitGenerator
extends AbstractSplitGenerator
implements RandomSplitGenerator

Picks the best binning algorithm from the provided ones.

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected adams.data.binning.algorithm.BinningAlgorithm[]	m_Algorithms	the algorithms to evaluate.
protected boolean	m_Generated	whether the split was generated.
protected adams.data.binning.algorithm.ManualBinning	m_Manual	for generating class distributions.
protected int	m_NumEvaluationBins	the number of evaluation bins.
protected double	m_Percentage	the percentage.
protected boolean	m_PreserveOrder	whether to preserve the order.

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
BestBinnedNumericClassRandomSplitGenerator()	Initializes the generator.
BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, adams.data.binning.algorithm.BinningAlgorithm[] algorithms, double percentage)	Initializes the generator.
BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, adams.data.binning.algorithm.BinningAlgorithm[] algorithms, long seed, double percentage)	Initializes the generator.
BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, adams.data.binning.algorithm.BinningAlgorithm[] algorithms, long seed, double percentage, boolean preserveOrder)	Initializes the generator.

Method Summary

Modifier and Type	Method	Description
String	algorithmsTipText()	Returns the tip text for this property.
protected double[]	calcDistribution(List<adams.data.binning.Binnable<weka.core.Instance>> binnable, double emptyBinValue)	Calculates the class distribution.
protected boolean	canRandomize()	Returns whether randomization is enabled.
protected boolean	checkNext()	Returns true if the iteration has more elements.
protected WekaTrainTestSetContainer	createNext()	Creates the next result.
void	defineOptions()	Adds options to the internal list of options.
protected void	doInitializeIterator()	Initializes the iterator.
adams.data.binning.algorithm.BinningAlgorithm[]	getAlgorithms()	Returns the binning algorithms to choose from.
int	getNumEvaluationBins()	Returns the number of bins to use during evaluation.
double	getPercentage()	Returns the split percentage.
boolean	getPreserveOrder()	Returns whether to preserve the order.
String	globalInfo()	Returns a string describing the object.
String	numEvaluationBinsTipText()	Returns the tip text for this property.
String	percentageTipText()	Returns the tip text for this property.
String	preserveOrderTipText()	Returns the tip text for this property.
void	setAlgorithms(adams.data.binning.algorithm.BinningAlgorithm[] value)	Sets the binning algorithms to choose from.
void	setNumEvaluationBins(int value)	Sets the number of bints to use during evaluation.
void	setPercentage(double value)	Sets the split percentage.
void	setPreserveOrder(boolean value)	Sets whether to preserve the order.

Methods inherited from class weka.classifiers.AbstractSplitGenerator

getData, getSeed, getUseViews, hasNext, initialize, initializeIterator, next, randomize, remove, reset, seedTipText, setData, setSeed, setUseViews, toString, 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, setData, toString

Field Detail

m_Percentage

protected double m_Percentage

the percentage.

m_PreserveOrder

protected boolean m_PreserveOrder

whether to preserve the order.

m_Algorithms

protected adams.data.binning.algorithm.BinningAlgorithm[] m_Algorithms

the algorithms to evaluate.

m_NumEvaluationBins

protected int m_NumEvaluationBins

the number of evaluation bins.

m_Generated

protected boolean m_Generated

whether the split was generated.

m_Manual

protected adams.data.binning.algorithm.ManualBinning m_Manual

for generating class distributions.

Constructor Detail

BestBinnedNumericClassRandomSplitGenerator

public BestBinnedNumericClassRandomSplitGenerator()

Initializes the generator.

BestBinnedNumericClassRandomSplitGenerator

public BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data,
                                                  adams.data.binning.algorithm.BinningAlgorithm[] algorithms,
                                                  long seed,
                                                  double percentage)

Initializes the generator. Does not preserve the order.

Parameters:

data - the dataset to split

algorithms - the binning algorithms to use

seed - the seed value to use for randomization

percentage - the percentage of the training set (0-1)

BestBinnedNumericClassRandomSplitGenerator

public BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data,
                                                  adams.data.binning.algorithm.BinningAlgorithm[] algorithms,
                                                  double percentage)

Initializes the generator. Preserves the order.

Parameters:

data - the dataset to split

algorithms - the binning algorithms to use

percentage - the percentage of the training set (0-1)

BestBinnedNumericClassRandomSplitGenerator

public BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data,
                                                  adams.data.binning.algorithm.BinningAlgorithm[] algorithms,
                                                  long seed,
                                                  double percentage,
                                                  boolean preserveOrder)

Initializes the generator.

Parameters:

data - the dataset to split

algorithms - the binning algorithms to use

seed - the seed value to use for randomization

percentage - the percentage of the training set (0-1)

preserveOrder - whether to preserve the order

Method Detail

globalInfo

public String globalInfo()

Returns a string describing the object.

Specified by:

globalInfo in interface adams.core.GlobalInfoSupporter

Specified by:

globalInfo in class adams.core.option.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 adams.core.option.OptionHandler

Overrides:

defineOptions in class AbstractSplitGenerator

setPercentage

public void setPercentage(double value)

Sets the split percentage.

Specified by:

setPercentage in interface adams.data.splitgenerator.RandomSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

setPercentage in interface RandomSplitGenerator

Parameters:

value - the percentage (0-1)

getPercentage

public double getPercentage()

Returns the split percentage.

Specified by:

getPercentage in interface adams.data.splitgenerator.RandomSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

getPercentage in interface RandomSplitGenerator

Returns:

the percentage (0-1)

percentageTipText

public String percentageTipText()

Returns the tip text for this property.

Returns:

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

setPreserveOrder

public void setPreserveOrder(boolean value)

Sets whether to preserve the order.

Specified by:

setPreserveOrder in interface adams.data.splitgenerator.RandomSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

setPreserveOrder in interface RandomSplitGenerator

Parameters:

value - true if to preserve order

getPreserveOrder

public boolean getPreserveOrder()

Returns whether to preserve the order.

Specified by:

getPreserveOrder in interface adams.data.splitgenerator.RandomSplitGenerator<weka.core.Instances,WekaTrainTestSetContainer>

Specified by:

getPreserveOrder in interface RandomSplitGenerator

Returns:

true if to preserve order

preserveOrderTipText

public String preserveOrderTipText()

Returns the tip text for this property.

Returns:

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

setAlgorithms

public void setAlgorithms(adams.data.binning.algorithm.BinningAlgorithm[] value)

Sets the binning algorithms to choose from.

Parameters:

value - the algorithms

getAlgorithms

public adams.data.binning.algorithm.BinningAlgorithm[] getAlgorithms()

Returns the binning algorithms to choose from.

Returns:

the algorithms

algorithmsTipText

public String algorithmsTipText()

Returns the tip text for this property.

Returns:

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

setNumEvaluationBins

public void setNumEvaluationBins(int value)

Sets the number of bints to use during evaluation.

Parameters:

value - the number of bins

getNumEvaluationBins

public int getNumEvaluationBins()

Returns the number of bins to use during evaluation.

Returns:

the number of bins

numEvaluationBinsTipText

public String numEvaluationBinsTipText()

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

doInitializeIterator

protected void doInitializeIterator()

Initializes the iterator.

Specified by:

doInitializeIterator in class AbstractSplitGenerator

See Also:

AbstractSplitGenerator.canRandomize()

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.

calcDistribution

protected double[] calcDistribution(List<adams.data.binning.Binnable<weka.core.Instance>> binnable,
                                    double emptyBinValue)

Calculates the class distribution.

Parameters:

binnable - the instances to calculate the distribution for

emptyBinValue - the value to use for empty bins

Returns:

the distribution

createNext

protected WekaTrainTestSetContainer createNext()

Creates the next result.

Specified by:

createNext in class AbstractSplitGenerator

Returns:

the next result