MetaCost

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.SingleClassifierEnhancer
  - - weka.classifiers.RandomizableSingleClassifierEnhancer
    - - weka.classifiers.meta.MetaCost

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler

public class MetaCost
extends RandomizableSingleClassifierEnhancer
implements TechnicalInformationHandler

This metaclassifier makes its base classifier cost-sensitive using the method specified in

Pedro Domingos: MetaCost: A general method for making classifiers cost-sensitive. In: Fifth International Conference on Knowledge Discovery and Data Mining, 155-164, 1999.

This classifier should produce similar results to one created by passing the base learner to Bagging, which is in turn passed to a CostSensitiveClassifier operating on minimum expected cost. The difference is that MetaCost produces a single cost-sensitive classifier of the base learner, giving the benefits of fast classification and interpretable output (if the base learner itself is interpretable). This implementation uses all bagging iterations when reclassifying training data (the MetaCost paper reports a marginal improvement when only those iterations containing each training instance are used in reclassifying that instance).

BibTeX:

 @inproceedings{Domingos1999,
    author = {Pedro Domingos},
    booktitle = {Fifth International Conference on Knowledge Discovery and Data Mining},
    pages = {155-164},
    title = {MetaCost: A general method for making classifiers cost-sensitive},
    year = {1999}
 }

Valid options are:

 -I <num>
  Number of bagging iterations.
  (default 10)

 -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.

 -P
  Size of each bag, as a percentage of the
  training set size. (default 100)

 -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: 1.24 $
Author:: Len Trigg (len@reeltwo.com)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`MATRIX_ON_DEMAND` load cost matrix on demand
`static int`	`MATRIX_SUPPLIED` use explicit matrix
`static Tag[]`	`TAGS_MATRIX_SOURCE` Specify possible sources of the cost matrix

Constructor Summary

Constructors
Constructor and Description

MetaCost()

Constructors
Constructor and Description
`MetaCost()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`bagSizePercentTipText()` Returns the tip text for this property
`void`	`buildClassifier(Instances data)` Builds the model of the base learner.
`java.lang.String`	`costMatrixSourceTipText()` Returns the tip text for this property
`java.lang.String`	`costMatrixTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance instance)` Classifies a given instance after filtering.
`int`	`getBagSizePercent()` Gets the size of each bag, as a percentage of the training set size.
`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.
`int`	`getNumIterations()` Gets the number of bagging iterations
`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.
`TechnicalInformation`	`getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`java.lang.String`	`globalInfo()` Returns a string describing classifier
`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`	`numIterationsTipText()` Returns the tip text for this property
`java.lang.String`	`onDemandDirectoryTipText()` Returns the tip text for this property
`void`	`setBagSizePercent(int newBagSizePercent)` Sets the size of each bag, as a percentage of the training set size.
`void`	`setCostMatrix(CostMatrix newCostMatrix)` Sets the misclassification cost matrix.
`void`	`setCostMatrixSource(SelectedTag newMethod)` Sets the source location of the cost matrix.
`void`	`setNumIterations(int numIterations)` Sets the number of bagging iterations
`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 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
  - MetaCost
```
public MetaCost()
```
- Method Detail
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    
    a description suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public TechnicalInformation getTechnicalInformation()
```
    Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - 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:
```
 -I <num>
  Number of bagging iterations.
  (default 10)
```
```
 -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.
```
```
 -P
  Size of each bag, as a percentage of the
  training set size. (default 100)
```
```
 -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
  - costMatrixSourceTipText
```
public java.lang.String costMatrixSourceTipText()
```
    Returns the tip text for this property
    
    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 the tip text for this property
    
    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.
  - bagSizePercentTipText
```
public java.lang.String bagSizePercentTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getBagSizePercent
```
public int getBagSizePercent()
```
    Gets the size of each bag, as a percentage of the training set size.
    
    Returns:
    
    the bag size, as a percentage.
  - setBagSizePercent
```
public void setBagSizePercent(int newBagSizePercent)
```
    Sets the size of each bag, as a percentage of the training set size.
    
    Parameters:
    
    newBagSizePercent - the bag size, as a percentage.
  - numIterationsTipText
```
public java.lang.String numIterationsTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setNumIterations
```
public void setNumIterations(int numIterations)
```
    Sets the number of bagging iterations
    
    Parameters:
    
    numIterations - the number of iterations to use
  - getNumIterations
```
public int getNumIterations()
```
    Gets the number of bagging iterations
    
    Returns:
    
    the maximum number of bagging iterations
  - costMatrixTipText
```
public java.lang.String costMatrixTipText()
```
    Returns the tip text for this property
    
    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
```
    Classifies a given instance after filtering.
    
    Overrides:
    
    distributionForInstance in class Classifier
    
    Parameters:
    
    instance - the instance to be classified
    
    Returns:
    
    the class distribution for the given instance
    
    Throws:
    
    java.lang.Exception - if instance could not be classified successfully
  - toString
```
public java.lang.String toString()
```
    Output a representation of this classifier
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a string representaiton 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]

Class MetaCost

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Field Detail

MATRIX_ON_DEMAND

MATRIX_SUPPLIED

TAGS_MATRIX_SOURCE

Constructor Detail

MetaCost

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

costMatrixSourceTipText

getCostMatrixSource

setCostMatrixSource

onDemandDirectoryTipText

getOnDemandDirectory

setOnDemandDirectory

bagSizePercentTipText

getBagSizePercent

setBagSizePercent

numIterationsTipText

setNumIterations

getNumIterations

costMatrixTipText

getCostMatrix

setCostMatrix

getCapabilities

buildClassifier

distributionForInstance

toString

getRevision

main