weka.classifiers
Class Classifier

java.lang.Object
  weka.classifiers.Classifier

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable

Direct Known Subclasses:

AdditiveRegression, ADTree, AODE, AttributeSelectedClassifier, BayesNet, ComplementNaiveBayes, ConjunctiveRule, CostSensitiveClassifier, DecisionStump, DecisionTable, Decorate, FilteredClassifier, FLR, HND, HyperPipes, IB1, IBk, Id3, J48, JRip, KStar, LBR, LeastMedSq, LinearRegression, LMT, Logistic, LogisticBase, M5Base, MultiClassClassifier, MultilayerPerceptron, MultipleClassifiersCombiner, NaiveBayes, NaiveBayesMultinomial, NaiveBayesSimple, ND, NNge, OneR, OrdinalClassClassifier, PaceRegression, PART, PreConstructedLinearModel, Prism, RacedIncrementalLogitBoost, RandomForest, RandomizableClassifier, RandomTree, RBFNetwork, REPTree, Ridor, RuleNode, SimpleLinearRegression, SimpleLogistic, SingleClassifierEnhancer, SMO, SMOreg, ThresholdSelector, TreeBasedMultiClassClassifier, UserClassifier, VFI, VotedPerceptron, Winnow, ZeroR

public abstract class Classifier

extends java.lang.Object

implements java.lang.Cloneable, java.io.Serializable, OptionHandler

Abstract classifier. All schemes for numeric or nominal prediction in Weka extend this class. Note that a classifier MUST either implement distributionForInstance() or classifyInstance().

Version:

$Revision: 1.10 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

protected boolean

m_Debug Whether the classifier is run in debug mode.

Constructor Summary

Classifier()

Method Summary

abstract void	buildClassifier(Instances data) Generates a classifier.
double	classifyInstance(Instance instance) Classifies the given test instance.
java.lang.String	debugTipText() Returns the tip text for this property
double[]	distributionForInstance(Instance instance) Predicts the class memberships for a given instance.
static Classifier	forName(java.lang.String classifierName, java.lang.String[] options) Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.
boolean	getDebug() Get whether debugging is turned on.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options.
static Classifier[]	makeCopies(Classifier model, int num) Creates copies of the current classifier, which can then be used for boosting etc.
void	setDebug(boolean debug) Set debugging mode.
void	setOptions(java.lang.String[] options) Parses a given list of options.

Methods inherited from class java.lang.Object

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

Field Detail

m_Debug

protected boolean m_Debug

Whether the classifier is run in debug mode.

Constructor Detail

Classifier

public Classifier()

Method Detail

buildClassifier

public abstract void buildClassifier(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.

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(Instance instance)
                        throws java.lang.Exception

Classifies the given test instance. The instance has to belong to a dataset when it's being classified. Note that a classifier MUST implement either this or distributionForInstance().

Parameters:

instance - the instance to be classified

Returns:

the predicted most likely class for the instance or Instance.missingValue() if no prediction is made

Throws:

java.lang.Exception - if an error occurred during the prediction

distributionForInstance

public double[] distributionForInstance(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. Note that a classifier MUST implement either this or classifyInstance().

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

forName

public static Classifier forName(java.lang.String classifierName,
                                 java.lang.String[] options)
                          throws java.lang.Exception

Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method. If the classifier implements OptionHandler and the options parameter is non-null, the classifier will have it's options set.

Parameters:

classifierName - the fully qualified class name of the classifier

options - an array of options suitable for passing to setOptions. May be null.

Returns:

the newly created classifier, ready for use.

Throws:

java.lang.Exception - if the classifier name is invalid, or the options supplied are not acceptable to the classifier

makeCopies

public static Classifier[] makeCopies(Classifier model,
                                      int num)
                               throws java.lang.Exception

Creates copies of the current classifier, which can then be used for boosting etc. Note that this method now uses Serialization to perform a deep copy, so the Classifier object must be fully Serializable. Any currently built model will now be copied as well.

Parameters:

model - an example classifier to copy

num - the number of classifiers copies to create.

Returns:

an array of classifiers.

Throws:

java.lang.Exception - if an error occurs

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

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:

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

Specified by:

setOptions in interface OptionHandler

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.

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions

setDebug

public void setDebug(boolean debug)

Set debugging mode.

Parameters:

debug - true if debug output should be printed

getDebug

public boolean getDebug()

Get whether debugging is turned on.

Returns:

true if debugging output is on

debugTipText

public java.lang.String debugTipText()

Returns the tip text for this property

Returns:

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