Package weka.classifiers.meta
Class CostSensitiveClassifier
- java.lang.Object
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- weka.classifiers.Classifier
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- weka.classifiers.SingleClassifierEnhancer
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- weka.classifiers.RandomizableSingleClassifierEnhancer
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- weka.classifiers.meta.CostSensitiveClassifier
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- 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
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Field Summary
Fields Modifier and Type Field Description static int
MATRIX_ON_DEMAND
load cost matrix on demandstatic int
MATRIX_SUPPLIED
use explicit cost matrixstatic Tag[]
TAGS_MATRIX_SOURCE
Specify possible sources of the cost matrix-
Fields inherited from interface weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
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Constructor Summary
Constructors Constructor Description CostSensitiveClassifier()
Default constructor.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description 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
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Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, setClassifier
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Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
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Field Detail
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MATRIX_ON_DEMAND
public static final int MATRIX_ON_DEMAND
load cost matrix on demand- See Also:
- Constant Field Values
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MATRIX_SUPPLIED
public static final int MATRIX_SUPPLIED
use explicit cost matrix- See Also:
- Constant Field Values
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TAGS_MATRIX_SOURCE
public static final Tag[] TAGS_MATRIX_SOURCE
Specify possible sources of the cost matrix
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Method Detail
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listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classRandomizableSingleClassifierEnhancer
- Returns:
- an enumeration of all the available options.
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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 interfaceOptionHandler
- Overrides:
setOptions
in classRandomizableSingleClassifierEnhancer
- Parameters:
options
- the list of options as an array of strings- Throws:
java.lang.Exception
- if an option is not supported
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of the Classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classRandomizableSingleClassifierEnhancer
- Returns:
- an array of strings suitable for passing to setOptions
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globalInfo
public java.lang.String globalInfo()
- Returns:
- a description of the classifier suitable for displaying in the explorer/experimenter gui
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costMatrixSourceTipText
public java.lang.String costMatrixSourceTipText()
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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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.
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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.
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onDemandDirectoryTipText
public java.lang.String onDemandDirectoryTipText()
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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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.
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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.
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minimizeExpectedCostTipText
public java.lang.String minimizeExpectedCostTipText()
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getMinimizeExpectedCost
public boolean getMinimizeExpectedCost()
Gets the value of MinimizeExpectedCost.- Returns:
- Value of MinimizeExpectedCost.
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setMinimizeExpectedCost
public void setMinimizeExpectedCost(boolean newMinimizeExpectedCost)
Set the value of MinimizeExpectedCost.- Parameters:
newMinimizeExpectedCost
- Value to assign to MinimizeExpectedCost.
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costMatrixTipText
public java.lang.String costMatrixTipText()
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getCostMatrix
public CostMatrix getCostMatrix()
Gets the misclassification cost matrix.- Returns:
- the cost matrix
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setCostMatrix
public void setCostMatrix(CostMatrix newCostMatrix)
Sets the misclassification cost matrix.- Parameters:
newCostMatrix
- the cost matrix
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getCapabilities
public Capabilities getCapabilities()
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classSingleClassifierEnhancer
- Returns:
- the capabilities of this classifier
- See Also:
Capabilities
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buildClassifier
public void buildClassifier(Instances data) throws java.lang.Exception
Builds the model of the base learner.- Specified by:
buildClassifier
in classClassifier
- Parameters:
data
- the training data- Throws:
java.lang.Exception
- if the classifier could not be built successfully
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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 classClassifier
- 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
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graphType
public int graphType()
Returns the type of graph this classifier represents.
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graph
public java.lang.String graph() throws java.lang.Exception
Returns graph describing the classifier (if possible).
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toString
public java.lang.String toString()
Output a representation of this classifier- Overrides:
toString
in classjava.lang.Object
- Returns:
- a string representation of the classifier
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
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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]
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