weka.classifiers.mi
Class MILR

java.lang.Object
  extended by weka.classifiers.Classifier
      extended by weka.classifiers.mi.MILR
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, MultiInstanceCapabilitiesHandler, OptionHandler, RevisionHandler

public class MILR
extends Classifier
implements OptionHandler, MultiInstanceCapabilitiesHandler

Uses either standard or collective multi-instance assumption, but within linear regression. For the collective assumption, it offers arithmetic or geometric mean for the posteriors.

Valid options are:

 -D
  Turn on debugging output.
 -R <ridge>
  Set the ridge in the log-likelihood.
 -A [0|1|2]
  Defines the type of algorithm:
   0. standard MI assumption
   1. collective MI assumption, arithmetic mean for posteriors
   2. collective MI assumption, geometric mean for posteriors

Version:
$Revision: 1.4 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
See Also:
Serialized Form

Field Summary
static int ALGORITHMTYPE_ARITHMETIC
          collective MI assumption, arithmetic mean for posteriors
static int ALGORITHMTYPE_DEFAULT
          standard MI assumption
static int ALGORITHMTYPE_GEOMETRIC
          collective MI assumption, geometric mean for posteriors
static Tag[] TAGS_ALGORITHMTYPE
          the types of algorithms
 
Constructor Summary
MILR()
           
 
Method Summary
 java.lang.String algorithmTypeTipText()
          Returns the tip text for this property
 void buildClassifier(Instances train)
          Builds the classifier
 double[] distributionForInstance(Instance exmp)
          Computes the distribution for a given exemplar
 SelectedTag getAlgorithmType()
          Gets the type of algorithm.
 Capabilities getCapabilities()
          Returns default capabilities of the classifier.
 Capabilities getMultiInstanceCapabilities()
          Returns the capabilities of this multi-instance classifier for the relational data.
 java.lang.String[] getOptions()
          Gets the current settings of the classifier.
 java.lang.String getRevision()
          Returns the revision string.
 double getRidge()
          Gets the ridge in the log-likelihood.
 java.lang.String globalInfo()
          Returns the tip text for this property
 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 ridgeTipText()
          Returns the tip text for this property
 void setAlgorithmType(SelectedTag newType)
          Sets the algorithm type.
 void setOptions(java.lang.String[] options)
          Parses a given list of options.
 void setRidge(double ridge)
          Sets the ridge in the log-likelihood.
 java.lang.String toString()
          Gets a string describing the classifier.
 
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

ALGORITHMTYPE_DEFAULT

public static final int ALGORITHMTYPE_DEFAULT
standard MI assumption

See Also:
Constant Field Values

ALGORITHMTYPE_ARITHMETIC

public static final int ALGORITHMTYPE_ARITHMETIC
collective MI assumption, arithmetic mean for posteriors

See Also:
Constant Field Values

ALGORITHMTYPE_GEOMETRIC

public static final int ALGORITHMTYPE_GEOMETRIC
collective MI assumption, geometric mean for posteriors

See Also:
Constant Field Values

TAGS_ALGORITHMTYPE

public static final Tag[] TAGS_ALGORITHMTYPE
the types of algorithms

Constructor Detail

MILR

public MILR()
Method Detail

globalInfo

public java.lang.String globalInfo()
Returns the tip text for this property

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

listOptions

public java.util.Enumeration listOptions()
Returns an enumeration describing the available options

Specified by:
listOptions in interface OptionHandler
Overrides:
listOptions in class Classifier
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.

Specified by:
setOptions in interface OptionHandler
Overrides:
setOptions in class Classifier
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 Classifier
Returns:
an array of strings suitable for passing to setOptions

ridgeTipText

public java.lang.String ridgeTipText()
Returns the tip text for this property

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

setRidge

public void setRidge(double ridge)
Sets the ridge in the log-likelihood.

Parameters:
ridge - the ridge

getRidge

public double getRidge()
Gets the ridge in the log-likelihood.

Returns:
the ridge

algorithmTypeTipText

public java.lang.String algorithmTypeTipText()
Returns the tip text for this property

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

getAlgorithmType

public SelectedTag getAlgorithmType()
Gets the type of algorithm.

Returns:
the algorithm type

setAlgorithmType

public void setAlgorithmType(SelectedTag newType)
Sets the algorithm type.

Parameters:
newType - the new algorithm type

getCapabilities

public Capabilities getCapabilities()
Returns default capabilities of the classifier.

Specified by:
getCapabilities in interface CapabilitiesHandler
Overrides:
getCapabilities in class Classifier
Returns:
the capabilities of this classifier
See Also:
Capabilities

getMultiInstanceCapabilities

public Capabilities getMultiInstanceCapabilities()
Returns the capabilities of this multi-instance classifier for the relational data.

Specified by:
getMultiInstanceCapabilities in interface MultiInstanceCapabilitiesHandler
Returns:
the capabilities of this object
See Also:
Capabilities

buildClassifier

public void buildClassifier(Instances train)
                     throws java.lang.Exception
Builds the classifier

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

distributionForInstance

public double[] distributionForInstance(Instance exmp)
                                 throws java.lang.Exception
Computes the distribution for a given exemplar

Overrides:
distributionForInstance in class Classifier
Parameters:
exmp - the exemplar for which distribution is computed
Returns:
the distribution
Throws:
java.lang.Exception - if the distribution can't be computed successfully

toString

public java.lang.String toString()
Gets a string describing the classifier.

Overrides:
toString in class java.lang.Object
Returns:
a string describing the classifer built.

getRevision

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

Specified by:
getRevision in interface RevisionHandler
Returns:
the revision

main

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

Parameters:
argv - should contain the command line arguments to the scheme (see Evaluation)