weka.filters.unsupervised.instance
Class RemoveMisclassifiedRel

java.lang.Object
  weka.filters.Filter
      weka.filters.unsupervised.instance.RemoveMisclassifiedRel

All Implemented Interfaces:

Serializable, weka.core.CapabilitiesHandler, weka.core.OptionHandler, weka.core.RevisionHandler, weka.filters.UnsupervisedFilter

public class RemoveMisclassifiedRel
extends weka.filters.Filter
implements weka.filters.UnsupervisedFilter, weka.core.OptionHandler

A filter that removes instances which are incorrectly classified. Useful for removing outliers.

Valid options are:

 -W <classifier specification>
  Full class name of classifier to use, followed
  by scheme options. eg:
   "weka.classifiers.bayes.NaiveBayes -D"
  (default: weka.classifiers.rules.ZeroR)

 -C <class index>
  Attribute on which misclassifications are based.
  If < 0 will use any current set class or default to the last attribute.

 -F <number of folds>
  The number of folds to use for cross-validation cleansing.
  (<2 = no cross-validation - default).

 -T <threshold>
  Threshold for the max error when predicting numeric class.
  (Value should be >= 0, default = 0.1).

 -I
  The maximum number of cleansing iterations to perform.
  (<1 = until fully cleansed - default)

 -V
  Invert the match so that correctly classified instances are discarded.
 

Version:

$Revision: 4584 $

Author:

Richard Kirkby (rkirkby@cs.waikato.ac.nz), Malcolm Ware (mfw4@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

protected int	m_classIndex The attribute to treat as the class for purposes of cleansing.
protected weka.classifiers.Classifier	m_cleansingClassifier The classifier used to do the cleansing
protected boolean	m_firstBatchFinished Have we processed the first batch (i.e.
protected boolean	m_invertMatching Whether to invert the match so the correctly classified instances are discarded
protected double	m_numericClassifyThreshold The threshold for deciding when a numeric value is correctly classified
protected double	m_numericClassifyThresholdAbs if Absolute error is less than this, then we're ok
protected int	m_numOfCleansingIterations The maximum number of cleansing iterations to perform (<1 = until fully cleansed)
protected int	m_numOfCrossValidationFolds The number of cross validation folds to perform (<2 = no cross validation)

Fields inherited from class weka.filters.Filter

m_FirstBatchDone, m_InputRelAtts, m_InputStringAtts, m_NewBatch, m_OutputRelAtts, m_OutputStringAtts

Constructor Summary

RemoveMisclassifiedRel()

Method Summary

String	absErrTipText() Returns the tip text for this property
boolean	batchFinished() Signify that this batch of input to the filter is finished.
String	classifierTipText() Returns the tip text for this property
String	classIndexTipText() Returns the tip text for this property
double	getAbsErr() Gets the threshold for the max error when predicting a numeric class.
weka.core.Capabilities	getCapabilities() Returns the Capabilities of this filter.
weka.classifiers.Classifier	getClassifier() Gets the classifier used by the filter.
protected String	getClassifierSpec() Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier.
int	getClassIndex() Gets the attribute on which misclassifications are based.
boolean	getInvert() Get whether selection is inverted.
int	getMaxIterations() Gets the maximum number of cleansing iterations performed
int	getNumFolds() Gets the number of cross-validation folds used by the filter.
String[]	getOptions() Gets the current settings of the filter.
String	getRevision() Returns the revision string.
double	getThreshold() Gets the threshold for the max error when predicting a numeric class.
String	globalInfo() Returns a string describing this filter
boolean	input(weka.core.Instance instance) Input an instance for filtering.
String	invertTipText() Returns the tip text for this property
Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for testing this class.
String	maxIterationsTipText() Returns the tip text for this property
String	numFoldsTipText() Returns the tip text for this property
void	setAbsErr(double threshold) Sets the threshold for the max error when predicting a numeric class.
void	setClassifier(weka.classifiers.Classifier classifier) Sets the classifier to classify instances with.
void	setClassIndex(int classIndex) Sets the attribute on which misclassifications are based.
boolean	setInputFormat(weka.core.Instances instanceInfo) Sets the format of the input instances.
void	setInvert(boolean invert) Set whether selection is inverted.
void	setMaxIterations(int iterations) Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed
void	setNumFolds(int numOfFolds) Sets the number of cross-validation folds to use - < 2 means no cross-validation.
void	setOptions(String[] options) Parses a given list of options.
void	setThreshold(double threshold) Sets the threshold for the max error when predicting a numeric class.
String	thresholdTipText() Returns the tip text for this property.

Methods inherited from class weka.filters.Filter

batchFilterFile, bufferInput, copyValues, copyValues, filterFile, flushInput, getCapabilities, getInputFormat, getOutputFormat, initInputLocators, initOutputLocators, inputFormatPeek, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, mayRemoveInstanceAfterFirstBatchDone, numPendingOutput, output, outputFormatPeek, outputPeek, push, resetQueue, runFilter, setOutputFormat, testInputFormat, toString, useFilter, wekaStaticWrapper

Methods inherited from class java.lang.Object

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

Field Detail

m_cleansingClassifier

protected weka.classifiers.Classifier m_cleansingClassifier

The classifier used to do the cleansing

m_classIndex

protected int m_classIndex

The attribute to treat as the class for purposes of cleansing.

m_numOfCrossValidationFolds

protected int m_numOfCrossValidationFolds

The number of cross validation folds to perform (<2 = no cross validation)

m_numOfCleansingIterations

protected int m_numOfCleansingIterations

The maximum number of cleansing iterations to perform (<1 = until fully cleansed)

m_numericClassifyThreshold

protected double m_numericClassifyThreshold

The threshold for deciding when a numeric value is correctly classified

m_numericClassifyThresholdAbs

protected double m_numericClassifyThresholdAbs

if Absolute error is less than this, then we're ok

m_invertMatching

protected boolean m_invertMatching

Whether to invert the match so the correctly classified instances are discarded

m_firstBatchFinished

protected boolean m_firstBatchFinished

Have we processed the first batch (i.e. training data)?

Constructor Detail

RemoveMisclassifiedRel

public RemoveMisclassifiedRel()

Method Detail

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns the Capabilities of this filter.

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.filters.Filter

Returns:

the capabilities of this object

See Also:

Capabilities

setInputFormat

public boolean setInputFormat(weka.core.Instances instanceInfo)
                       throws Exception

Sets the format of the input instances.

Overrides:

setInputFormat in class weka.filters.Filter

Parameters:

instanceInfo - an Instances object containing the input instance structure (any instances contained in the object are ignored - only the structure is required).

Returns:

true if the outputFormat may be collected immediately

Throws:

Exception - if the inputFormat can't be set successfully

input

public boolean input(weka.core.Instance instance)
              throws Exception

Input an instance for filtering.

Overrides:

input in class weka.filters.Filter

Parameters:

instance - the input instance

Returns:

true if the filtered instance may now be collected with output().

Throws:

NullPointerException - if the input format has not been defined.

Exception - if the input instance was not of the correct format or if there was a problem with the filtering.

batchFinished

public boolean batchFinished()
                      throws Exception

Signify that this batch of input to the filter is finished.

Overrides:

batchFinished in class weka.filters.Filter

Returns:

true if there are instances pending output

Throws:

IllegalStateException - if no input structure has been defined

Exception

listOptions

public Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface weka.core.OptionHandler

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:

 -W <classifier specification>
  Full class name of classifier to use, followed
  by scheme options. eg:
   "weka.classifiers.bayes.NaiveBayes -D"
  (default: weka.classifiers.rules.ZeroR)

 -C <class index>
  Attribute on which misclassifications are based.
  If < 0 will use any current set class or default to the last attribute.

 -F <number of folds>
  The number of folds to use for cross-validation cleansing.
  (<2 = no cross-validation - default).

 -T <threshold>
  Threshold for the max error when predicting numeric class.
  (Value should be >= 0, default = 0.1).

 -I
  The maximum number of cleansing iterations to perform.
  (<1 = until fully cleansed - default)

 -V
  Invert the match so that correctly classified instances are discarded.
 

Specified by:

setOptions in interface weka.core.OptionHandler

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 filter.

Specified by:

getOptions in interface weka.core.OptionHandler

Returns:

an array of strings suitable for passing to setOptions

globalInfo

public String globalInfo()

Returns a string describing this filter

Returns:

a description of the filter suitable for displaying in the explorer/experimenter gui

classifierTipText

public String classifierTipText()

Returns the tip text for this property

Returns:

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

setClassifier

public void setClassifier(weka.classifiers.Classifier classifier)

Sets the classifier to classify instances with.

Parameters:

classifier - The classifier to be used (with its options set).

getClassifier

public weka.classifiers.Classifier getClassifier()

Gets the classifier used by the filter.

Returns:

The classifier to be used.

getClassifierSpec

protected String getClassifierSpec()

Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier.

Returns:

the classifier string.

classIndexTipText

public String classIndexTipText()

Returns the tip text for this property

Returns:

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

setClassIndex

public void setClassIndex(int classIndex)

Sets the attribute on which misclassifications are based. If < 0 will use any current set class or default to the last attribute.

Parameters:

classIndex - the class index.

getClassIndex

public int getClassIndex()

Gets the attribute on which misclassifications are based.

Returns:

the class index.

numFoldsTipText

public String numFoldsTipText()

Returns the tip text for this property

Returns:

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

setNumFolds

public void setNumFolds(int numOfFolds)

Sets the number of cross-validation folds to use - < 2 means no cross-validation.

Parameters:

numOfFolds - the number of folds.

getNumFolds

public int getNumFolds()

Gets the number of cross-validation folds used by the filter.

Returns:

the number of folds.

absErrTipText

public String absErrTipText()

Returns the tip text for this property

Returns:

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

setAbsErr

public void setAbsErr(double threshold)

Sets the threshold for the max error when predicting a numeric class. The value should be >= 0.

Parameters:

threshold - the numeric theshold.

getAbsErr

public double getAbsErr()

Gets the threshold for the max error when predicting a numeric class.

Returns:

the numeric threshold.

thresholdTipText

public String thresholdTipText()

Returns the tip text for this property.

Returns:

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

setThreshold

public void setThreshold(double threshold)

Sets the threshold for the max error when predicting a numeric class. The value should be >= 0.

Parameters:

threshold - the numeric theshold.

getThreshold

public double getThreshold()

Gets the threshold for the max error when predicting a numeric class.

Returns:

the numeric threshold.

maxIterationsTipText

public String maxIterationsTipText()

Returns the tip text for this property

Returns:

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

setMaxIterations

public void setMaxIterations(int iterations)

Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed

Parameters:

iterations - the maximum number of iterations.

getMaxIterations

public int getMaxIterations()

Gets the maximum number of cleansing iterations performed

Returns:

the maximum number of iterations.

invertTipText

public String invertTipText()

Returns the tip text for this property

Returns:

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

setInvert

public void setInvert(boolean invert)

Set whether selection is inverted.

Parameters:

invert - whether or not to invert selection.

getInvert

public boolean getInvert()

Get whether selection is inverted.

Returns:

whether or not selection is inverted.

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.filters.Filter

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - should contain arguments to the filter: use -h for help