weka.classifiers.lazy

Class IB1

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.lazy.IB1

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 IB1
extends weka.classifiers.AbstractClassifier
implements weka.classifiers.UpdateableClassifier, weka.core.TechnicalInformationHandler

Nearest-neighbour classifier. Uses normalized Euclidean distance to find the training instance closest to the given test instance, and predicts the same class as this training instance. If multiple instances have the same (smallest) distance to the test instance, the first one found is used.

For more information, see

D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.

BibTeX:

 @article{Aha1991,
    author = {D. Aha and D. Kibler},
    journal = {Machine Learning},
    pages = {37-66},
    title = {Instance-based learning algorithms},
    volume = {6},
    year = {1991}
 }
 

Valid options are:

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

Version:

$Revision: 10390 $

Author:

Stuart Inglis (singlis@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.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
IB1()

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(weka.core.Instances instances) Generates the classifier.
double	classifyInstance(weka.core.Instance instance) Classifies the given test instance.
weka.core.Capabilities	getCapabilities() Returns default capabilities of the classifier.
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
static void	main(java.lang.String[] argv) Main method for testing this class.
java.lang.String	toString() Returns a description of this classifier.
void	updateClassifier(weka.core.Instance instance) Updates the classifier.

Methods inherited from class weka.classifiers.AbstractClassifier

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

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

IB1

public IB1()

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 instances)
                     throws java.lang.Exception

Generates the classifier.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

instances - set of instances serving as training data

Throws:

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

updateClassifier

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

Updates the classifier.

Specified by:

updateClassifier in interface weka.classifiers.UpdateableClassifier

Parameters:

instance - the instance to be put into the classifier

Throws:

java.lang.Exception - if the instance could not be included successfully

classifyInstance

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

Classifies the given test instance.

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

the predicted class for the instance

Throws:

java.lang.Exception - if the instance can't be classified

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.

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).