weka.classifiers.rules

Class NNge

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.rules.NNge

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.classifiers.UpdateableClassifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

public class NNge
extends weka.classifiers.AbstractClassifier
implements weka.classifiers.UpdateableClassifier, weka.core.OptionHandler, weka.core.TechnicalInformationHandler

Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules). For more information, see

Brent Martin (1995). Instance-Based learning: Nearest Neighbor With Generalization. Hamilton, New Zealand.

Sylvain Roy (2002). Nearest Neighbor With Generalization. Christchurch, New Zealand.

BibTeX:

 @mastersthesis{Martin1995,
    address = {Hamilton, New Zealand},
    author = {Brent Martin},
    school = {University of Waikato},
    title = {Instance-Based learning: Nearest Neighbor With Generalization},
    year = {1995}
 }
 
 @unpublished{Roy2002,
    address = {Christchurch, New Zealand},
    author = {Sylvain Roy},
    school = {University of Canterbury},
    title = {Nearest Neighbor With Generalization},
    year = {2002}
 }
 

Valid options are:

 -G <value>
  Number of attempts of generalisation.
 

 -I <value>
  Number of folder for computing the mutual information.
 

Version:

$Revision: 8108 $

Author:

Brent Martin (bim20@cosc.canterbury.ac.nz), Sylvain Roy (sro33@student.canterbury.ac.nz)

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
NNge()

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(weka.core.Instances data) Generates a classifier.
double	classifyInstance(weka.core.Instance instance) Classifies a given instance.
weka.core.Capabilities	getCapabilities() Returns default capabilities of the classifier.
int	getNumAttemptsOfGeneOption() Gets the number of attempts for generalisation.
int	getNumFoldersMIOption() Gets the number of folder for mutual information.
java.lang.String[]	getOptions() Gets the current option settings for the OptionHandler.
java.lang.String	getRevision() Returns the revision string.
weka.core.TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
java.lang.String	globalInfo() Returns a string describing classifier
java.util.Enumeration	listOptions() Returns an enumeration of all the available options..
static void	main(java.lang.String[] argv) Main method for testing this class.
java.lang.String	numAttemptsOfGeneOptionTipText() Returns the tip text for this property
java.lang.String	numFoldersMIOptionTipText() Returns the tip text for this property
void	setNumAttemptsOfGeneOption(int newIntParameter) Sets the number of attempts for generalisation.
void	setNumFoldersMIOption(int newIntParameter) Sets the number of folder for mutual information.
void	setOptions(java.lang.String[] options) Sets the OptionHandler's options using the given list.
java.lang.String	toString() Returns a description of this classifier.
void	updateClassifier(weka.core.Instance instance) Updates the classifier using the given instance.

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

NNge

public NNge()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

getTechnicalInformation

public weka.core.TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface weka.core.TechnicalInformationHandler

Returns:

the technical information about this class

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.classifiers.AbstractClassifier

Returns:

the capabilities of this classifier

buildClassifier

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

Generates a classifier. Must initialize all fields of the classifier that are not being set via options (ie. multiple calls of buildClassifier must always lead to the same result). Must not change the dataset in any way.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if the classifier has not been generated successfully

classifyInstance

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

Classifies a given instance.

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

index of the predicted class as a double

Throws:

java.lang.Exception - if instance could not be classified successfully

updateClassifier

public void updateClassifier(weka.core.Instance instance)
                      throws java.lang.Exception

Updates the classifier using the given instance.

Specified by:

updateClassifier in interface weka.classifiers.UpdateableClassifier

Parameters:

instance - the instance to include

Throws:

java.lang.Exception - if instance could not be incorporated successfully

toString

public java.lang.String toString()

Returns a description of this classifier.

Overrides:

toString in class java.lang.Object

Returns:

a description of this classifier as a string.

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration of all the available options..

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class weka.classifiers.AbstractClassifier

Returns:

an enumeration of all available options.

setOptions

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

 -G <value>
  Number of attempts of generalisation.
 

 -I <value>
  Number of folder for computing the mutual information.
 

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.classifiers.AbstractClassifier

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.String[] getOptions()

Gets the current option settings for the OptionHandler.

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.AbstractClassifier

Returns:

the list of current option settings as an array of strings

numAttemptsOfGeneOptionTipText

public java.lang.String numAttemptsOfGeneOptionTipText()

Returns the tip text for this property

Returns:

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

getNumAttemptsOfGeneOption

public int getNumAttemptsOfGeneOption()

Gets the number of attempts for generalisation.

Returns:

the value of the option G

setNumAttemptsOfGeneOption

public void setNumAttemptsOfGeneOption(int newIntParameter)

Sets the number of attempts for generalisation.

Parameters:

newIntParameter - the new value.

numFoldersMIOptionTipText

public java.lang.String numFoldersMIOptionTipText()

Returns the tip text for this property

Returns:

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

getNumFoldersMIOption

public int getNumFoldersMIOption()

Gets the number of folder for mutual information.

Returns:

the value of the option I

setNumFoldersMIOption

public void setNumFoldersMIOption(int newIntParameter)

Sets the number of folder for mutual information.

Parameters:

newIntParameter - the new value.

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

main

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

Main method for testing this class.

Parameters:

argv - should contain command line arguments for evaluation (see Evaluation).