meka.classifiers.multilabel.neurofuzzy

Class WvARAM

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass

meka.classifiers.multilabel.neurofuzzy.WvARAM

All Implemented Interfaces:

Serializable, Cloneable, IncrementalMultiLabelClassifier, MultiLabelClassifier, MultiLabelClassifierThreaded, weka.classifiers.Classifier, weka.classifiers.UpdateableClassifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.Randomizable, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler, weka.core.WeightedInstancesHandler

public class WvARAM
extends ARAMNetworkClass
implements weka.core.OptionHandler, weka.core.WeightedInstancesHandler, weka.classifiers.UpdateableClassifier, weka.core.Randomizable, weka.core.TechnicalInformationHandler, MultiLabelClassifier

****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION. Class for a ML-ARAM classifier.

* Valid options are:

-P
Use a different generalization value.

-K
Use ML rankings to class.

-V
Define the number of voters.

Version:

$Revision: 1.0 $

Author:

Fernando Benites (Fernando.Benites@uni.konstanz.de)

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	WvARAM.BuildClassifier
class	WvARAM.DistributionCalc
class	WvARAM.DistributionCalcM

Field Summary

Fields

Modifier and Type	Field and Description
protected String	activity_report

Fields inherited from class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass

neuronsactivated, neuronsactivity, numFeatures, threshold

Fields inherited from class weka.classifiers.SingleClassifierEnhancer

m_Classifier

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 and Description
WvARAM()
WvARAM(int fnumberofnetworks)

Method Summary

Modifier and Type	Method and Description
double[]	ARAMm_Ranking2Class(double[] rankings)
void	buildClassifier(weka.core.Instances D) Generates the classifier.
double	classifyInstance(weka.core.Instance instance) Classifies the given test instance.
String	debugTipText() Returns the tip text for this property
void	destroy()
double[]	distributionForInstance(weka.core.Instance instance) Calculates the class membership probabilities for the given test instance.
double[][]	distributionForInstanceM(weka.core.Instances inst)
String	fastLearnTipText()
void	freeNetworks()
weka.core.Capabilities	getCapabilities()
boolean	getDebug() Get whether debugging is turned on.
boolean	getFastLearn()
String	getModel() Returns a string representation of the model.
boolean	getNeuronsActivity()
String	getNeuronsActivityFileName()
String[]	getOptions() Gets the current settings of the classifier.
int	getSeed()
boolean	getSparse()
boolean	getSparseH()
boolean	getSparseHT()
weka.core.TechnicalInformation	getTechnicalInformation()
boolean	getThreadedVoters()
double	getThreshold()
double	getVigilancy()
int	getVoters()
String	globalInfo() Description to display in the GUI.
boolean	isThreaded()
Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for testing this class.
String	neuronsActivityFileNameTipText()
String	neuronsActivityTipText()
String	seedTipText()
void	setDebug(boolean debug) Set debugging mode.
void	setFastLearn(boolean ffastaram)
void	setNeuronsActivity(boolean fsaveneuronsactivity)
void	setNeuronsActivityFileName(String ffsna)
void	setOptions(String[] options) Parses a given list of options.
void	setSeed(int seed)
void	setSparse(boolean fsparsearam)
void	setSparseH(boolean fsparsearam)
void	setSparseHT(boolean fsparsearam)
void	setThreaded(boolean setv)
void	setThreadedVoters(boolean fThreadedVoters)
void	setThreshold(double fthreshold)
void	setVigilancy(double vigilancy)
void	setVoters(int fvoter)
String	sparseHTipText()
String	sparseHTTipText()
String	sparseTipText()
String	threadedTipText()
String	threadedVotersTipText()
String	thresholdTipText()
String	toString() Returns a description of the classifier.
void	updateClassifier(weka.core.Instance instance)
String	vigilancyTipText()
String	votersTipText()

Methods inherited from class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass

testCapabilities

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, defaultClassifierOptions, defaultClassifierString, getClassifier, getClassifierSpec, postExecution, preExecution, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

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

Field Detail

activity_report

protected String activity_report

Constructor Detail

WvARAM

public WvARAM(int fnumberofnetworks)

WvARAM

public WvARAM()

Method Detail

buildClassifier

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

Generates the classifier.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

instances - set of instances serving as training data

Throws:

Exception - if the classifier has not been generated successfully

distributionForInstance

public double[] distributionForInstance(weka.core.Instance instance)
                                 throws Exception

Calculates the class membership probabilities for the given test instance.

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

predicted class probability distribution

Throws:

Exception - if there is a problem generating the prediction

ARAMm_Ranking2Class

public double[] ARAMm_Ranking2Class(double[] rankings)

classifyInstance

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

Classifies the given test instance. The instance has to belong to a dataset when it's being classified. Note that a classifier MUST implement either this or distributionForInstance().

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

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.SingleClassifierEnhancer

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options. Valid options are:

-K
Use kernel estimation for modelling numeric attributes rather than a single normal distribution.

-D
Use supervised discretization to process numeric attributes.

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.classifiers.SingleClassifierEnhancer

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Gets the current settings of the classifier.

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.SingleClassifierEnhancer

Returns:

an array of strings suitable for passing to setOptions

toString

public String toString()

Returns a description of the classifier.

Overrides:

toString in class Object

Returns:

a description of the classifier as a string.

globalInfo

public String globalInfo()

Description to display in the GUI.

Returns:

the description

getTechnicalInformation

public weka.core.TechnicalInformation getTechnicalInformation()

Specified by:

getTechnicalInformation in interface weka.core.TechnicalInformationHandler

updateClassifier

public void updateClassifier(weka.core.Instance instance)
                      throws Exception

Specified by:

updateClassifier in interface weka.classifiers.UpdateableClassifier

Throws:

Exception

setSeed

public void setSeed(int seed)

Specified by:

setSeed in interface weka.core.Randomizable

getSeed

public int getSeed()

Specified by:

getSeed in interface weka.core.Randomizable

getThreadedVoters

public boolean getThreadedVoters()

setThreadedVoters

public void setThreadedVoters(boolean fThreadedVoters)

getFastLearn

public boolean getFastLearn()

setFastLearn

public void setFastLearn(boolean ffastaram)

getSparse

public boolean getSparse()

setSparse

public void setSparse(boolean fsparsearam)

getSparseH

public boolean getSparseH()

setSparseHT

public void setSparseHT(boolean fsparsearam)

getSparseHT

public boolean getSparseHT()

setSparseH

public void setSparseH(boolean fsparsearam)

getVoters

public int getVoters()

setVoters

public void setVoters(int fvoter)

getVigilancy

public double getVigilancy()

setVigilancy

public void setVigilancy(double vigilancy)

setThreshold

public void setThreshold(double fthreshold)

getThreshold

public double getThreshold()

getNeuronsActivity

public boolean getNeuronsActivity()

setNeuronsActivity

public void setNeuronsActivity(boolean fsaveneuronsactivity)

getNeuronsActivityFileName

public String getNeuronsActivityFileName()

setNeuronsActivityFileName

public void setNeuronsActivityFileName(String ffsna)

freeNetworks

public void freeNetworks()

destroy

public void destroy()

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options

distributionForInstanceM

public double[][] distributionForInstanceM(weka.core.Instances inst)
                                    throws Exception

Specified by:

distributionForInstanceM in interface MultiLabelClassifierThreaded

Throws:

Exception

setDebug

public void setDebug(boolean debug)

Description copied from interface: MultiLabelClassifier

Set debugging mode.

Specified by:

setDebug in interface MultiLabelClassifier

Overrides:

setDebug in class weka.classifiers.AbstractClassifier

Parameters:

debug - true if debug output should be printed

getDebug

public boolean getDebug()

Description copied from interface: MultiLabelClassifier

Get whether debugging is turned on.

Specified by:

getDebug in interface MultiLabelClassifier

Overrides:

getDebug in class weka.classifiers.AbstractClassifier

Returns:

true if debugging output is on

debugTipText

public String debugTipText()

Description copied from interface: MultiLabelClassifier

Returns the tip text for this property

Specified by:

debugTipText in interface MultiLabelClassifier

Overrides:

debugTipText in class weka.classifiers.AbstractClassifier

Returns:

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

getModel

public String getModel()

Description copied from interface: MultiLabelClassifier

Returns a string representation of the model.

Specified by:

getModel in interface MultiLabelClassifier

Returns:

the model

getCapabilities

public weka.core.Capabilities getCapabilities()

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.classifiers.SingleClassifierEnhancer

isThreaded

public boolean isThreaded()

Specified by:

isThreaded in interface MultiLabelClassifierThreaded

setThreaded

public void setThreaded(boolean setv)

Specified by:

setThreaded in interface MultiLabelClassifierThreaded

thresholdTipText

public String thresholdTipText()

fastLearnTipText

public String fastLearnTipText()

neuronsActivityTipText

public String neuronsActivityTipText()

neuronsActivityFileNameTipText

public String neuronsActivityFileNameTipText()

sparseTipText

public String sparseTipText()

sparseHTipText

public String sparseHTipText()

sparseHTTipText

public String sparseHTTipText()

seedTipText

public String seedTipText()

threadedTipText

public String threadedTipText()

threadedVotersTipText

public String threadedVotersTipText()

vigilancyTipText

public String vigilancyTipText()

votersTipText

public String votersTipText()