meka.classifiers.multilabel

Class ProblemTransformationMethod

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

meka.classifiers.multilabel.ProblemTransformationMethod

All Implemented Interfaces:

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

Direct Known Subclasses:

AbstractNeuralNet, BR, BRq, CC, CCq, CDN, EM, FW, LC, MBR, MetaProblemTransformationMethod, MULAN, RT, SubsetMapper

public abstract class ProblemTransformationMethod
extends weka.classifiers.SingleClassifierEnhancer
implements MultiLabelClassifier

MultilabelClassifier.java - A Multilabel Classifier.

Version:

Jan 2015

Author:

Jesse Read

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected weka.core.Instances	m_InstancesTemplate A Template for Problem Transformations

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
ProblemTransformationMethod()

Method Summary

Modifier and Type	Method and Description
abstract void	buildClassifier(weka.core.Instances trainingSet)
protected String	defaultClassifierString()
abstract double[]	distributionForInstance(weka.core.Instance i)
static void	evaluation(MultiLabelClassifier h, String[] args) Called by classifier's main() method upon initialisation from the command line.
weka.core.Capabilities	getCapabilities()
String	getModel() Returns a string representation of the model.
String	getRevision()
weka.core.Instances	getTemplate()
String	globalInfo() Description to display in the GUI.
static MultiLabelClassifier[]	makeCopies(MultiLabelClassifier model, int num) Creates a given number of deep copies of the given multi-label classifier using serialization.
static void	runClassifier(MultiLabelClassifier h, String[] args) Called by classifier's main() method upon initialisation from the command line.
void	testCapabilities(weka.core.Instances D) TestCapabilities.
String	toString()

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, defaultClassifierOptions, getClassifier, getClassifierSpec, getOptions, listOptions, postExecution, preExecution, setClassifier, setOptions

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, debugTipText, 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 meka.classifiers.multilabel.MultiLabelClassifier

debugTipText, getDebug, setDebug

Methods inherited from interface weka.classifiers.Classifier

classifyInstance

Methods inherited from interface weka.core.OptionHandler

getOptions, listOptions, setOptions

Field Detail

m_InstancesTemplate

protected weka.core.Instances m_InstancesTemplate

A Template for Problem Transformations

Constructor Detail

ProblemTransformationMethod

public ProblemTransformationMethod()

Method Detail

globalInfo

public String globalInfo()

Description to display in the GUI.

Returns:

the description

defaultClassifierString

protected String defaultClassifierString()

Overrides:

defaultClassifierString in class weka.classifiers.SingleClassifierEnhancer

toString

public String toString()

Overrides:

toString in class Object

getModel

public String getModel()

Returns a string representation of the model.

Specified by:

getModel in interface MultiLabelClassifier

Returns:

the model

getTemplate

public weka.core.Instances getTemplate()

testCapabilities

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

TestCapabilities. Make sure the training data is suitable.

Parameters:

D - the data

Throws:

Exception

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

buildClassifier

public abstract void buildClassifier(weka.core.Instances trainingSet)
                              throws Exception

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Throws:

Exception

distributionForInstance

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

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class weka.classifiers.AbstractClassifier

Throws:

Exception

getRevision

public String getRevision()

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

makeCopies

public static MultiLabelClassifier[] makeCopies(MultiLabelClassifier model,
                                                int num)
                                         throws Exception

Creates a given number of deep copies of the given multi-label classifier using serialization.

Parameters:

model - the classifier to copy

num - the number of classifier copies to create.

Returns:

an array of classifiers.

Throws:

Exception - if an error occurs

evaluation

public static void evaluation(MultiLabelClassifier h,
                              String[] args)

Called by classifier's main() method upon initialisation from the command line. TODO: In the future Use runClassifier(h,args) directly, and depreciated this function.

Parameters:

h - A classifier

args - Command-line options.

runClassifier

public static void runClassifier(MultiLabelClassifier h,
                                 String[] args)

Called by classifier's main() method upon initialisation from the command line.

Parameters:

h - A classifier

args - Command-line options.