weka.classifiers.meta
Class AbstainAttributePercentile

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.SingleClassifierEnhancer
          weka.classifiers.meta.AbstainAttributePercentile

All Implemented Interfaces:

Serializable, Cloneable, weka.classifiers.Classifier, weka.core.CapabilitiesHandler, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.WeightedInstancesHandler

public class AbstainAttributePercentile
extends weka.classifiers.SingleClassifierEnhancer
implements weka.core.WeightedInstancesHandler

Only predict if attribute value within percentile range. Ensure same for training set if req.

Version:

$Revision: 5710 $

Author:

Dale

See Also:

Serialized Form

Field Summary

protected int	m_attnum
protected weka.core.Instances	m_Data
protected boolean	m_debug
protected double	m_max
protected double	m_min
protected boolean	m_ok
protected double	m_pctile
protected Range	m_Range
protected Hashtable<Integer,double[]>	m_Ranges the ranges (attribute index <-> double[]).
protected boolean	m_removetrain

Fields inherited from class weka.classifiers.SingleClassifierEnhancer

m_Classifier

Fields inherited from class weka.classifiers.AbstractClassifier

m_Debug

Constructor Summary

AbstainAttributePercentile()

Method Summary

String	attributeTipText()
void	buildClassifier(weka.core.Instances data) Builds the classifier.
double	classifyInstance(weka.core.Instance inst) Returns the prediction.
String	getAttribute()
weka.core.Capabilities	getCapabilities() Returns default capabilities of the base classifier.
String[]	getOptions() Gets the current option settings for the OptionHandler.
double	getPercentile()
boolean	getRemoveTrain()
String	getRevision()
String	globalInfo() Returns a string describing classifier.
Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for running this class.
String	percentileTipText()
String	removeTrainTipText()
void	setAttribute(String at)
void	setOptions(String[] options) Sets the OptionHandler's options using the given list.
void	setPercentile(double var)
void	setRemoveTrain(boolean t)
String	toString() Returns description of classifier.

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, defaultClassifierString, getClassifier, getClassifierSpec, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

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

Methods inherited from class java.lang.Object

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

Field Detail

m_Data

protected weka.core.Instances m_Data

m_attnum

protected int m_attnum

m_debug

protected boolean m_debug

m_pctile

protected double m_pctile

m_ok

protected boolean m_ok

m_removetrain

protected boolean m_removetrain

m_min

protected double m_min

m_max

protected double m_max

m_Ranges

protected Hashtable<Integer,double[]> m_Ranges

the ranges (attribute index <-> double[]).

m_Range

protected Range m_Range

Constructor Detail

AbstainAttributePercentile

public AbstainAttributePercentile()

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.SingleClassifierEnhancer

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible). 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.rules.ZeroR)

 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

 -S <sint>
  Number of regressions
  (default: 10)
 

 -P <int>
  Percent sample size
  (default: 60)
 

 -E <int>
  Percent Error at
  (default: 50)
 

 -G <seed>
  Set the seed used to generate samples
  (default: 0)
 

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 option settings for the OptionHandler.

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.SingleClassifierEnhancer

Returns:

the list of current option settings as an array of strings

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the base classifier.

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.classifiers.SingleClassifierEnhancer

Returns:

the capabilities of the base classifier

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

classifyInstance

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

Returns the prediction.

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Throws:

Exception

toString

public String toString()

Returns description of classifier.

Overrides:

toString in class Object

getRevision

public String getRevision()

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

setPercentile

public void setPercentile(double var)

getPercentile

public double getPercentile()

percentileTipText

public String percentileTipText()

setAttribute

public void setAttribute(String at)

getAttribute

public String getAttribute()

attributeTipText

public String attributeTipText()

setRemoveTrain

public void setRemoveTrain(boolean t)

getRemoveTrain

public boolean getRemoveTrain()

removeTrainTipText

public String removeTrainTipText()

main

public static void main(String[] argv)

Main method for running this class.

Parameters:

argv - the options