Package weka.classifiers.meta

Class MOA

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.meta.MOA

All Implemented Interfaces:

weka.classifiers.UpdateableClassifier

public class MOA
extends weka.classifiers.AbstractClassifier
implements weka.classifiers.UpdateableClassifier

Wrapper for MOA classifiers.

Since MOA doesn't offer a mechanism to query a classifier for the types of attributes and classes it can handle, the capabilities of this wrapper are hard-coded: nominal and numeric attributes and only nominal class attributes are allowed.

Valid options are:

 -B <classname + options>
  The MOA classifier to use.
  (default: moa.classifiers.DecisionStump)

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

Version:

$Revision$

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected WekaToSamoaInstanceConverter	instanceConverter
protected Classifier	m_ActualClassifier	the actual moa classifier to use for learning.
protected ClassOption	m_Classifier	the moa classifier option (this object is used in the GenericObjectEditor).

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
MOA()

Method Summary

Modifier and Type	Method	Description
void	buildClassifier(weka.core.Instances data)	Generates a classifier.
java.lang.String	classifierTipText()	Returns the tooltip displayed in the GUI.
double[]	distributionForInstance(weka.core.Instance instance)	Predicts the class memberships for a given instance.
weka.core.Capabilities	getCapabilities()	Returns the Capabilities of this classifier.
ClassOption	getClassifier()	Returns the current MOA classifier in use.
java.lang.String[]	getOptions()	Gets the current settings of the Classifier.
java.lang.String	getRevision()	Returns the revision string.
java.lang.String	globalInfo()	Returns a string describing the classifier.
java.util.Enumeration	listOptions()	Returns an enumeration describing the available options.
static void	main(java.lang.String[] args)	Main method for testing this class.
void	setClassifier(ClassOption value)	Sets the MOA classifier to use.
void	setOptions(java.lang.String[] options)	Parses a given list of options.
java.lang.String	toString()	Returns a string representation of the model.
void	updateClassifier(weka.core.Instance instance)	Updates a classifier using the given instance.

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, debugTipText, 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

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

Field Detail

m_ActualClassifier

protected Classifier m_ActualClassifier

the actual moa classifier to use for learning.

m_Classifier

protected ClassOption m_Classifier

the moa classifier option (this object is used in the GenericObjectEditor).

instanceConverter

protected WekaToSamoaInstanceConverter instanceConverter

Constructor Detail

MOA

public MOA()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing the classifier.

Returns:

a description suitable for displaying in the explorer/experimenter gui

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Overrides:

listOptions in class weka.classifiers.AbstractClassifier

Returns:

an enumeration of all the available options.

setOptions

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

Parses a given list of options.

Valid options are:

 -B <classname + options>
  The MOA classifier to use.
  (default: moa.classifiers.trees.DecisionStump)

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

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 settings of the Classifier.

Overrides:

getOptions in class weka.classifiers.AbstractClassifier

Returns:

an array of strings suitable for passing to setOptions

setClassifier

public void setClassifier(ClassOption value)

Sets the MOA classifier to use.

Parameters:

value - the classifier to use

getClassifier

public ClassOption getClassifier()

Returns the current MOA classifier in use.

Returns:

the classifier in use

classifierTipText

public java.lang.String classifierTipText()

Returns the tooltip displayed in the GUI.

Returns:

the tooltip

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns the Capabilities of this classifier. Maximally permissive capabilities are allowed by default. MOA doesn't specify what

Overrides:

getCapabilities in class weka.classifiers.AbstractClassifier

Returns:

the capabilities of this object

See Also:

Capabilities

buildClassifier

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

Generates a classifier.

Parameters:

data - 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 a classifier using the given instance.

Specified by:

updateClassifier in interface weka.classifiers.UpdateableClassifier

Parameters:

instance - the instance to included

Throws:

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

distributionForInstance

public double[] distributionForInstance(weka.core.Instance instance)
                                 throws java.lang.Exception

Predicts the class memberships for a given instance. If an instance is unclassified, the returned array elements must be all zero. If the class is numeric, the array must consist of only one element, which contains the predicted value.

Overrides:

distributionForInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction

Throws:

java.lang.Exception - if distribution could not be computed successfully

getRevision

public java.lang.String getRevision()

Returns the revision string.

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

toString

public java.lang.String toString()

Returns a string representation of the model.

Overrides:

toString in class java.lang.Object

Returns:

the string representation

main

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

Main method for testing this class.

Parameters:

args - the options