Package weka.classifiers.mi

Class MILR

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.mi.MILR
All Implemented Interfaces:
Serializable, 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: 9144 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
See Also:

  • Field Details

    • ALGORITHMTYPE_DEFAULT

      public static final int ALGORITHMTYPE_DEFAULT
      standard MI assumption
      See Also:

    • ALGORITHMTYPE_ARITHMETIC

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

    • ALGORITHMTYPE_GEOMETRIC

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

    • TAGS_ALGORITHMTYPE

      public static final Tag[] TAGS_ALGORITHMTYPE
      the types of algorithms

  • Constructor Details

    • MILR

      public MILR()

  • Method Details

    • globalInfo

      public 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 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(String[] options) throws 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:
      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 Classifier
      Returns:
      an array of strings suitable for passing to setOptions

    • ridgeTipText

      public 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 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:

    • 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:

    • buildClassifier

      public void buildClassifier(Instances train) throws Exception
      Builds the classifier
      Specified by:
      buildClassifier in class Classifier
      Parameters:
      train - the training data to be used for generating the boosted classifier.
      Throws:
      Exception - if the classifier could not be built successfully

    • distributionForInstance

      public double[] distributionForInstance(Instance exmp) throws 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:
      Exception - if the distribution can't be computed successfully

    • toString

      public String toString()
      Gets a string describing the classifier.
      Overrides:
      toString in class Object
      Returns:
      a string describing the classifer built.

    • getRevision

      public 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(String[] argv)
      Main method for testing this class.
      Parameters:
      argv - should contain the command line arguments to the scheme (see Evaluation)