weka.classifiers.meta
Class CostSensitiveClassifier

java.lang.Object
  extended by weka.classifiers.Classifier
      extended by weka.classifiers.SingleClassifierEnhancer
          extended by weka.classifiers.RandomizableSingleClassifierEnhancer
              extended by weka.classifiers.meta.CostSensitiveClassifier
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, 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: 1.29 $
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.
 java.lang.String costMatrixSourceTipText()
           
 java.lang.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.
 java.io.File getOnDemandDirectory()
          Returns the directory that will be searched for cost files when loading on demand.
 java.lang.String[] getOptions()
          Gets the current settings of the Classifier.
 java.lang.String getRevision()
          Returns the revision string.
 java.lang.String globalInfo()
           
 java.lang.String graph()
          Returns graph describing the classifier (if possible).
 int graphType()
          Returns the type of graph this classifier represents.
 java.util.Enumeration listOptions()
          Returns an enumeration describing the available options.
static void main(java.lang.String[] argv)
          Main method for testing this class.
 java.lang.String minimizeExpectedCostTipText()
           
 java.lang.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(java.io.File newDir)
          Sets the directory that will be searched for cost files when loading on demand.
 void setOptions(java.lang.String[] options)
          Parses a given list of options.
 java.lang.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.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, 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 java.util.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(java.lang.String[] options)
                throws java.lang.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:
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
Overrides:
getOptions in class RandomizableSingleClassifierEnhancer
Returns:
an array of strings suitable for passing to setOptions

globalInfo

public java.lang.String globalInfo()
Returns:
a description of the classifier suitable for displaying in the explorer/experimenter gui

costMatrixSourceTipText

public java.lang.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 java.lang.String onDemandDirectoryTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui

getOnDemandDirectory

public java.io.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(java.io.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 java.lang.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 java.lang.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 CapabilitiesHandler
Overrides:
getCapabilities in class SingleClassifierEnhancer
Returns:
the capabilities of this classifier
See Also:
Capabilities

buildClassifier

public void buildClassifier(Instances data)
                     throws java.lang.Exception
Builds the model of the base learner.

Specified by:
buildClassifier in class Classifier
Parameters:
data - the training data
Throws:
java.lang.Exception - if the classifier could not be built successfully

distributionForInstance

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

Overrides:
distributionForInstance in class Classifier
Parameters:
instance - the instance to be classified
Returns:
the computed distribution for the given instance
Throws:
java.lang.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 java.lang.String graph()
                       throws java.lang.Exception
Returns graph describing the classifier (if possible).

Specified by:
graph in interface Drawable
Returns:
the graph of the classifier in dotty format
Throws:
java.lang.Exception - if the classifier cannot be graphed

toString

public java.lang.String toString()
Output a representation of this classifier

Overrides:
toString in class java.lang.Object
Returns:
a string representation of the classifier

getRevision

public java.lang.String getRevision()
Returns the revision string.

Specified by:
getRevision in interface RevisionHandler
Overrides:
getRevision in class Classifier
Returns:
the revision

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

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