meka.classifiers.multilabel

Class MCC

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

meka.classifiers.multilabel.MultilabelClassifier

meka.classifiers.multilabel.CC

meka.classifiers.multilabel.MCC

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.core.CapabilitiesHandler, weka.core.OptionHandler, weka.core.Randomizable, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

Direct Known Subclasses:

CT, PMCC

public class MCC
extends CC
implements weka.core.TechnicalInformationHandler

MCC.java - CC with Monte Carlo optimisation. Note inference is now a bit slower than reported in the paper,
Jesse Read, Luca Martino, David Luengo. Efficient Monte Carlo Optimization for Multi-dimensional Classifier Chains. http://arxiv.org/abs/1211.2190. 2012
There we used a faster implementation, full of ugly hacks, but it got broken when I updated CC.java.
This version extends CC, and thus is a bit cleaner, but for some reason inference is quite slower than expected with high m_Iy.
TODO Option for hold-out set, instead of training and testing on training data (internally).

Version:

April 2014

Author:

Jesse Read

See Also:

CC, Serialized Form

Constructor Summary

Constructors

Constructor and Description
MCC()

Method Summary

Methods

Modifier and Type	Method and Description
void	buildClassifier(weka.core.Instances D)
double[]	distributionForInstance(weka.core.Instance x)
int	getChainIterations() Get the iterations of s (chain order)
int	getInferenceInterations() Get the inference iterations
java.lang.String[]	getOptions()
weka.core.TechnicalInformation	getTechnicalInformation()
java.lang.String	globalInfo() Description to display in the GUI.
double	likelihood(CC h, weka.core.Instances D) Likelihood - Return a default score of h evaluated on D.
double	likelihood(CC h, weka.core.Instances D, int payoff_fn) Likelihood - Return a score of choice (payoff_fn) of h evaluated on D.
java.util.Enumeration	listOptions()
static void	main(java.lang.String[] args)
void	setChainIterations(int is) Set the iterations of s (chain order)
void	setInferenceInterations(int iy) Set the inference iterations
void	setOptions(java.lang.String[] options)

Methods inherited from class meka.classifiers.multilabel.CC

getChain, getConfidences, getSeed, getTransformTemplates, probabilityForInstance, rebuildClassifier, sampleForInstance, sampleForInstanceFast, setChain, setSeed, transformInstance

Methods inherited from class meka.classifiers.multilabel.MultilabelClassifier

evaluation, getCapabilities, getRevision, getTemplate, makeCopies, runClassifier, testCapabilities, toString

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

MCC

public MCC()

Method Detail

likelihood

public double likelihood(CC h,
                weka.core.Instances D)
                  throws java.lang.Exception

Likelihood - Return a default score of h evaluated on D. sum ( p(y_i | x_i, h_s) ) TODO: use meka.core.Metrics

Throws:

java.lang.Exception

likelihood

public double likelihood(CC h,
                weka.core.Instances D,
                int payoff_fn)
                  throws java.lang.Exception

Likelihood - Return a score of choice (payoff_fn) of h evaluated on D. maximizing likelihood is the same as minimizing the error .. TODO: use meka.core.Metrics

Returns:

sum log P(Y|X;h) where h defines e.g., a particular chain order

Throws:

java.lang.Exception

buildClassifier

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

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Overrides:

buildClassifier in class CC

Throws:

java.lang.Exception

distributionForInstance

public double[] distributionForInstance(weka.core.Instance x)
                                 throws java.lang.Exception

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class CC

Throws:

java.lang.Exception

listOptions

public java.util.Enumeration listOptions()

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class weka.classifiers.SingleClassifierEnhancer

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.classifiers.SingleClassifierEnhancer

Throws:

java.lang.Exception

getOptions

public java.lang.String[] getOptions()

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.SingleClassifierEnhancer

setInferenceInterations

public void setInferenceInterations(int iy)

Set the inference iterations

getInferenceInterations

public int getInferenceInterations()

Get the inference iterations

setChainIterations

public void setChainIterations(int is)

Set the iterations of s (chain order)

getChainIterations

public int getChainIterations()

Get the iterations of s (chain order)

globalInfo

public java.lang.String globalInfo()

Description copied from class: CC

Description to display in the GUI.

Overrides:

globalInfo in class CC

Returns:

the description

getTechnicalInformation

public weka.core.TechnicalInformation getTechnicalInformation()

Specified by:

getTechnicalInformation in interface weka.core.TechnicalInformationHandler

Overrides:

getTechnicalInformation in class CC

main

public static void main(java.lang.String[] args)