Package weka.classifiers.meta

Class Corr

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

weka.classifiers.meta.Corr

All Implemented Interfaces:

Serializable, Cloneable, 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 Corr
extends weka.classifiers.SingleClassifierEnhancer
implements weka.core.WeightedInstancesHandler

Assume NO MISSING VALUES, all attributes must be NUMERIC (or 0/1 maybe ...). Simple attribute selection for regression: select k most correlated attrs ...

Valid options are:

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.functions.LinearRegression)

 Options specific to classifier weka.classifiers.rules.ZeroR:
 

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

 -K <int>
  The number of attrs. (default: 0 = numEx/2)

Version:

$Revision$

Author:

???

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected int	m_classIndex
protected double[]	m_coeffs
protected int	m_k
protected weka.filters.unsupervised.attribute.Remove	m_remove
protected int[]	m_subset

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	Description
Corr()

Method Summary

Modifier and Type	Method	Description
void	buildClassifier(weka.core.Instances data)	Builds the classifier.
double	classifyInstance(weka.core.Instance instance)	Returns the prediction.
protected String	defaultClassifierString()	String describing default classifier.
double[]	getCoeffs()
int	getNumattrs()
String[]	getOptions()	Gets the current settings of the Classifier.
String	getRevision()
int[]	getSubset()
weka.core.Instances	getSubset(weka.core.Instances data)
String	globalInfo()	Returns a string describing classifier.
String	keepIndices(weka.core.Instances data)
String	keepIndicesBasedOnCorrelation(weka.core.Instances data)
Enumeration	listOptions()	Returns an enumeration describing the available options.
static void	main(String[] argv)	Main method for testing this class.
double[]	means(weka.core.Instances data)
double[]	msq(weka.core.Instances data)
String	numattrsTipText()	Returns the tip text for this property.
double[]	sampleCorrs(weka.core.Instances data)
double[]	sampleDevs(weka.core.Instances data, double[] mean)
void	saveObject(Object o)
void	setNumattrs(int k)
void	setOptions(String[] options)	Parses a given list of options.
double[]	sumXY(weka.core.Instances data)
String	toString()	Returns description of classifier.

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

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

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

Field Detail

m_remove

protected weka.filters.unsupervised.attribute.Remove m_remove

m_classIndex

protected int m_classIndex

m_k

protected int m_k

m_subset

protected int[] m_subset

m_coeffs

protected double[] m_coeffs

Constructor Detail

Corr

public Corr()

Method Detail

defaultClassifierString

protected String defaultClassifierString()

String describing default classifier.

Overrides:

defaultClassifierString in class weka.classifiers.SingleClassifierEnhancer

Returns:

the default classifier

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.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:

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.functions.LinearRegression)

 Options specific to classifier weka.classifiers.rules.ZeroR:
 

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

 -K <int>
  The number of attrs. (default: 0 = numEx/2)

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

getNumattrs

public int getNumattrs()

setNumattrs

public void setNumattrs(int k)

numattrsTipText

public String numattrsTipText()

Returns the tip text for this property.

Returns:

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

sampleCorrs

public double[] sampleCorrs(weka.core.Instances data)

sumXY

public double[] sumXY(weka.core.Instances data)

sampleDevs

public double[] sampleDevs(weka.core.Instances data,
                           double[] mean)

msq

public double[] msq(weka.core.Instances data)

means

public double[] means(weka.core.Instances data)

keepIndices

public String keepIndices(weka.core.Instances data)

keepIndicesBasedOnCorrelation

public String keepIndicesBasedOnCorrelation(weka.core.Instances data)

getSubset

public weka.core.Instances getSubset(weka.core.Instances data)
                              throws Exception

Throws:

Exception

buildClassifier

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

Builds the classifier.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

data - the training data

Throws:

Exception - if something goes wrong

saveObject

public void saveObject(Object o)
                throws Exception

Throws:

Exception

classifyInstance

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

Returns the prediction.

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to classify

Returns:

the prediction

Throws:

Exception - if prediction fails

getCoeffs

public double[] getCoeffs()

getSubset

public int[] getSubset()

toString

public String toString()

Returns description of classifier.

Overrides:

toString in class Object

Returns:

the model

getRevision

public String getRevision()

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

main

public static void main(String[] argv)
                 throws Exception

Main method for testing this class.

Parameters:

argv - the options

Throws:

Exception