Package weka.classifiers.mi

Class MDD

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, MultiInstanceCapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler
    public class MDD
extends Classifier
implements OptionHandler, MultiInstanceCapabilitiesHandler, TechnicalInformationHandler
    Modified Diverse Density algorithm, with collective assumption.

    More information about DD:

    Oded Maron (1998). Learning from ambiguity.

    O. Maron, T. Lozano-Perez (1998). A Framework for Multiple Instance Learning. Neural Information Processing Systems. 10.

    BibTeX: 

     @phdthesis{Maron1998,
    author = {Oded Maron},
    school = {Massachusetts Institute of Technology},
    title = {Learning from ambiguity},
    year = {1998}
 }
 
 @article{Maron1998,
    author = {O. Maron and T. Lozano-Perez},
    journal = {Neural Information Processing Systems},
    title = {A Framework for Multiple Instance Learning},
    volume = {10},
    year = {1998}
 }

    Valid options are: 

     -D
  Turn on debugging output.
     -N <num>
  Whether to 0=normalize/1=standardize/2=neither.
  (default 1=standardize)
    Version:
    $Revision: 9144 $
    Author:
    Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
    See Also:
    Serialized Form

    • Field Detail

      • FILTER_NORMALIZE

        public static final int FILTER_NORMALIZE
        Normalize training data
        See Also:
        Constant Field Values

      • FILTER_STANDARDIZE

        public static final int FILTER_STANDARDIZE
        Standardize training data
        See Also:
        Constant Field Values

      • FILTER_NONE

        public static final int FILTER_NONE
        No normalization/standardization
        See Also:
        Constant Field Values

      • TAGS_FILTER

        public static final Tag[] TAGS_FILTER
        The filter to apply to the training data

    • Constructor Detail

      • MDD

        public MDD()

    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing this filter
        Returns:
        a description of the filter 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 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

      • filterTypeTipText

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

      • getFilterType

        public SelectedTag getFilterType()
        Gets how the training data will be transformed. Will be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
        Returns:
        the filtering mode

      • setFilterType

        public void setFilterType​(SelectedTag newType)
        Sets how the training data will be transformed. Should be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
        Parameters:
        newType - the new filtering mode

      • 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.

      • 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)