weka.classifiers.meta
Class CostSensitiveClassifier

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.SingleClassifierEnhancer
          weka.classifiers.RandomizableSingleClassifierEnhancer
              weka.classifiers.meta.CostSensitiveClassifier

All Implemented Interfaces:

Serializable, Cloneable, Classifier, CapabilitiesHandler, Drawable, OptionHandler, Randomizable, RevisionHandler

public class CostSensitiveClassifier
extends RandomizableSingleClassifierEnhancer
implements OptionHandler, Drawable

A metaclassifier that makes its base classifier cost-sensitive. Two methods can be used to introduce cost-sensitivity: reweighting training instances according to the total cost assigned to each class; or predicting the class with minimum expected misclassification cost (rather than the most likely class). Performance can often be improved by using a Bagged classifier to improve the probability estimates of the base classifier.

Valid options are:

 -M
  Minimize expected misclassification cost. Default is to
  reweight training instances according to costs per class

 -C <cost file name>
  File name of a cost matrix to use. If this is not supplied,
  a cost matrix will be loaded on demand. The name of the
  on-demand file is the relation name of the training data
  plus ".cost", and the path to the on-demand file is
  specified with the -N option.

 -N <directory>
  Name of a directory to search for cost files when loading
  costs on demand (default current directory).

 -cost-matrix <matrix>
  The cost matrix in Matlab single line format.

 -S <num>
  Random number seed.
  (default 1)

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.rules.ZeroR)

 
 Options specific to classifier weka.classifiers.rules.ZeroR:
 

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

Options after -- are passed to the designated classifier.

Version:

$Revision: 8034 $

Author:

Len Trigg (len@reeltwo.com)

See Also:

Serialized Form

Field Summary

static int	MATRIX_ON_DEMAND load cost matrix on demand
static int	MATRIX_SUPPLIED use explicit cost matrix
static Tag[]	TAGS_MATRIX_SOURCE Specify possible sources of the cost matrix

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

CostSensitiveClassifier()
Default constructor.

Method Summary

void	buildClassifier(Instances data) Builds the model of the base learner.
String	costMatrixSourceTipText()
String	costMatrixTipText()
double[]	distributionForInstance(Instance instance) Returns class probabilities.
Capabilities	getCapabilities() Returns default capabilities of the classifier.
CostMatrix	getCostMatrix() Gets the misclassification cost matrix.
SelectedTag	getCostMatrixSource() Gets the source location method of the cost matrix.
boolean	getMinimizeExpectedCost() Gets the value of MinimizeExpectedCost.
File	getOnDemandDirectory() Returns the directory that will be searched for cost files when loading on demand.
String[]	getOptions() Gets the current settings of the Classifier.
String	getRevision() Returns the revision string.
String	globalInfo()
String	graph() Returns graph describing the classifier (if possible).
int	graphType() Returns the type of graph this classifier represents.
Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for testing this class.
String	minimizeExpectedCostTipText()
String	onDemandDirectoryTipText()
void	setCostMatrix(CostMatrix newCostMatrix) Sets the misclassification cost matrix.
void	setCostMatrixSource(SelectedTag newMethod) Sets the source location of the cost matrix.
void	setMinimizeExpectedCost(boolean newMinimizeExpectedCost) Set the value of MinimizeExpectedCost.
void	setOnDemandDirectory(File newDir) Sets the directory that will be searched for cost files when loading on demand.
void	setOptions(String[] options) Parses a given list of options.
String	toString() Output a representation of this classifier

Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer

getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object

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

Field Detail

MATRIX_ON_DEMAND

public static final int MATRIX_ON_DEMAND

load cost matrix on demand

See Also:

Constant Field Values

MATRIX_SUPPLIED

public static final int MATRIX_SUPPLIED

use explicit cost matrix

See Also:

Constant Field Values

TAGS_MATRIX_SOURCE

public static final Tag[] TAGS_MATRIX_SOURCE

Specify possible sources of the cost matrix

Constructor Detail

CostSensitiveClassifier

public CostSensitiveClassifier()

Default constructor.

Method Detail

listOptions

public Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class RandomizableSingleClassifierEnhancer

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:

 -M
  Minimize expected misclassification cost. Default is to
  reweight training instances according to costs per class

 -C <cost file name>
  File name of a cost matrix to use. If this is not supplied,
  a cost matrix will be loaded on demand. The name of the
  on-demand file is the relation name of the training data
  plus ".cost", and the path to the on-demand file is
  specified with the -N option.

 -N <directory>
  Name of a directory to search for cost files when loading
  costs on demand (default current directory).

 -cost-matrix <matrix>
  The cost matrix in Matlab single line format.

 -S <num>
  Random number seed.
  (default 1)

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.rules.ZeroR)

 
 Options specific to classifier weka.classifiers.rules.ZeroR:
 

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

Options after -- are passed to the designated classifier.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class RandomizableSingleClassifierEnhancer

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 Classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class RandomizableSingleClassifierEnhancer

Returns:

an array of strings suitable for passing to setOptions

globalInfo

public String globalInfo()

Returns:

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

costMatrixSourceTipText

public String costMatrixSourceTipText()

Returns:

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

getCostMatrixSource

public SelectedTag getCostMatrixSource()

Gets the source location method of the cost matrix. Will be one of MATRIX_ON_DEMAND or MATRIX_SUPPLIED.

Returns:

the cost matrix source.

setCostMatrixSource

public void setCostMatrixSource(SelectedTag newMethod)

Sets the source location of the cost matrix. Values other than MATRIX_ON_DEMAND or MATRIX_SUPPLIED will be ignored.

Parameters:

newMethod - the cost matrix location method.

onDemandDirectoryTipText

public String onDemandDirectoryTipText()

Returns:

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

getOnDemandDirectory

public File getOnDemandDirectory()

Returns the directory that will be searched for cost files when loading on demand.

Returns:

The cost file search directory.

setOnDemandDirectory

public void setOnDemandDirectory(File newDir)

Sets the directory that will be searched for cost files when loading on demand.

Parameters:

newDir - The cost file search directory.

minimizeExpectedCostTipText

public String minimizeExpectedCostTipText()

Returns:

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

getMinimizeExpectedCost

public boolean getMinimizeExpectedCost()

Gets the value of MinimizeExpectedCost.

Returns:

Value of MinimizeExpectedCost.

setMinimizeExpectedCost

public void setMinimizeExpectedCost(boolean newMinimizeExpectedCost)

Set the value of MinimizeExpectedCost.

Parameters:

newMinimizeExpectedCost - Value to assign to MinimizeExpectedCost.

costMatrixTipText

public String costMatrixTipText()

Returns:

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

getCostMatrix

public CostMatrix getCostMatrix()

Gets the misclassification cost matrix.

Returns:

the cost matrix

setCostMatrix

public void setCostMatrix(CostMatrix newCostMatrix)

Sets the misclassification cost matrix.

Parameters:

newCostMatrix - the cost matrix

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface Classifier

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class SingleClassifierEnhancer

Returns:

the capabilities of this classifier

See Also:

Capabilities

buildClassifier

public void buildClassifier(Instances data)
                     throws Exception

Builds the model of the base learner.

Specified by:

buildClassifier in interface Classifier

Parameters:

data - the training data

Throws:

Exception - if the classifier could not be built successfully

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws Exception

Returns class probabilities. When minimum expected cost approach is chosen, returns probability one for class with the minimum expected misclassification cost. Otherwise it returns the probability distribution returned by the base classifier.

Specified by:

distributionForInstance in interface Classifier

Overrides:

distributionForInstance in class AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

the computed distribution for the given instance

Throws:

Exception - if instance could not be classified successfully

graphType

public int graphType()

Returns the type of graph this classifier represents.

Specified by:

graphType in interface Drawable

Returns:

the type of graph this classifier represents

graph

public String graph()
             throws Exception

Returns graph describing the classifier (if possible).

Specified by:

graph in interface Drawable

Returns:

the graph of the classifier in dotty format

Throws:

Exception - if the classifier cannot be graphed

toString

public String toString()

Output a representation of this classifier

Overrides:

toString in class Object

Returns:

a string representation of the classifier

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - should contain the following arguments: -t training file [-T test file] [-c class index]