Package weka.classifiers.meta

Class AbstainAverageWithClassifierWeights

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.MultipleClassifiersCombiner

weka.classifiers.meta.AbstainAverageWithClassifierWeights

All Implemented Interfaces:

Serializable, Cloneable, AbstainingClassifier, weka.classifiers.Classifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.WeightedInstancesHandler

public class AbstainAverageWithClassifierWeights
extends weka.classifiers.MultipleClassifiersCombiner
implements weka.core.WeightedInstancesHandler, AbstainingClassifier

Average base classifiers, abstain if difference outside thresholds

Valid options are:

Version:

$Revision: 12763 $

Author:

Dale

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected double[]	m_ClassifierWeights
protected String	m_ClassifierWeights_string
protected boolean[]	m_IsPercent
protected double	m_MaxDifference
protected double[]	m_MaxDifferences
protected String	m_MaxDifferences_string
protected double[]	m_Maxes
protected double[]	m_Mins

Fields inherited from class weka.classifiers.MultipleClassifiersCombiner

m_Classifiers

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor	Description
AbstainAverageWithClassifierWeights()

Method Summary

Modifier and Type	Method	Description
void	buildClassifier(weka.core.Instances data)	Buildclassifier builds all sub-classifiers
boolean	canAbstain()	Whether abstaining is possible, e.g., used in meta-classifiers.
protected boolean	checkOK(double avgPrediction, double difference)	Check prediction difference against thresholds
protected double	classificationNumericAverage(weka.core.Instance instance, boolean abstain)	Do the classification.
String	classifierWeightsTipText()	Returns the tip text for this property
double	classifyInstance(weka.core.Instance instance)	Classifies the given test instance.
protected String	diffToString()	Convert thresholds from array to string
double	getAbstentionClassification(weka.core.Instance inst)	The prediction that made the classifier abstain.
double[]	getAbstentionDistribution(weka.core.Instance inst)	The class distribution that made the classifier abstain.
weka.core.Capabilities	getCapabilities()	Returns default capabilities of the classifier.
String	getClassifierWeights()
String	getMaxDifference()	gets number of samples
String[]	getOptions()	Gets the current settings of Vote.
String	getRevision()	Returns the revision string.
String	globalInfo()	Returns a string describing classifier
Enumeration	listOptions()	Returns an enumeration describing the available options.
static void	main(String[] argv)	Main method for testing this class.
String	maxDifferenceTipText()	Returns the tip text for this property
protected void	parseString(String input)	Expect ; separated entries with min,max,difference e.g.
protected void	parseWeights(String input)	Expect "1,1,1,1"
void	setClassifierWeights(String s)
void	setMaxDifference(String s)
void	setOptions(String[] options)	Parses a given list of options.
String	toString()	Output a representation of this classifier

Methods inherited from class weka.classifiers.MultipleClassifiersCombiner

classifiersTipText, getClassifier, getClassifiers, getClassifierSpec, postExecution, preExecution, setClassifiers

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.classifiers.Classifier

distributionForInstance

Field Detail

m_MaxDifference

protected double m_MaxDifference

m_MaxDifferences

protected double[] m_MaxDifferences

m_Mins

protected double[] m_Mins

m_Maxes

protected double[] m_Maxes

m_IsPercent

protected boolean[] m_IsPercent

m_MaxDifferences_string

protected String m_MaxDifferences_string

m_ClassifierWeights

protected double[] m_ClassifierWeights

m_ClassifierWeights_string

protected String m_ClassifierWeights_string

Constructor Detail

AbstainAverageWithClassifierWeights

public AbstainAverageWithClassifierWeights()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

listOptions

public Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class weka.classifiers.MultipleClassifiersCombiner

Returns:

an enumeration of all the available options.

getOptions

public String[] getOptions()

Gets the current settings of Vote.

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.MultipleClassifiersCombiner

Returns:

an array of strings suitable for passing to setOptions()

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

 -S <num>
  Random number seed.
  (default 1)

 -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.classifiers.MultipleClassifiersCombiner

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Overrides:

getCapabilities in class weka.classifiers.MultipleClassifiersCombiner

Returns:

the capabilities of this classifier

buildClassifier

public void buildClassifier(weka.core.Instances data)
                     throws Exception

Buildclassifier builds all sub-classifiers

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

data - the training data to be used for generating the boosted classifier.

Throws:

Exception - if the classifier could not be built successfully

classifyInstance

public double classifyInstance(weka.core.Instance instance)
                        throws Exception

Classifies the given test instance.

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

the predicted most likely class for the instance or Instance.missingValue() if no prediction is made

Throws:

Exception - if an error occurred during the prediction

checkOK

protected boolean checkOK(double avgPrediction,
                          double difference)

Check prediction difference against thresholds

Parameters:

avgPrediction -

difference -

Returns:

parseWeights

protected void parseWeights(String input)

Expect "1,1,1,1"

Parameters:

input -

parseString

protected void parseString(String input)

Expect ; separated entries with min,max,difference e.g. 0-50,6;50-100,10%;100-200,20

Parameters:

input -

diffToString

protected String diffToString()

Convert thresholds from array to string

Returns:

classificationNumericAverage

protected double classificationNumericAverage(weka.core.Instance instance,
                                              boolean abstain)
                                       throws Exception

Do the classification. Abstain (or not) depending on flag

Parameters:

instance -

abstain -

Returns:

Throws:

Exception

toString

public String toString()

Output a representation of this classifier

Overrides:

toString in class Object

Returns:

a string representation of the classifier

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - should contain the following arguments: -t training file [-T test file] [-c class index]

canAbstain

public boolean canAbstain()

Whether abstaining is possible, e.g., used in meta-classifiers.

Specified by:

canAbstain in interface AbstainingClassifier

Returns:

true if abstaining is possible

getAbstentionClassification

public double getAbstentionClassification(weka.core.Instance inst)
                                   throws Exception

The prediction that made the classifier abstain.

Specified by:

getAbstentionClassification in interface AbstainingClassifier

Parameters:

inst - the instance to get the prediction for

Returns:

the prediction

Throws:

Exception - if fails to make prediction

getAbstentionDistribution

public double[] getAbstentionDistribution(weka.core.Instance inst)
                                   throws Exception

Description copied from interface: AbstainingClassifier

The class distribution that made the classifier abstain.

Specified by:

getAbstentionDistribution in interface AbstainingClassifier

Parameters:

inst - the instance to get the prediction for

Returns:

the class distribution

Throws:

Exception - if fails to make prediction

classifierWeightsTipText

public String classifierWeightsTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getClassifierWeights

public String getClassifierWeights()

setClassifierWeights

public void setClassifierWeights(String s)

maxDifferenceTipText

public String maxDifferenceTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getMaxDifference

public String getMaxDifference()

gets number of samples

Returns:

value

setMaxDifference

public void setMaxDifference(String s)