Package weka.classifiers.meta

Class RotationForest

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler
    public class RotationForest
extends RandomizableIteratedSingleClassifierEnhancer
implements WeightedInstancesHandler, TechnicalInformationHandler
    Class for construction a Rotation Forest. Can do classification and regression depending on the base learner.

    For more information, see

    Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630. URL http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211.

    BibTeX: 

     @article{Rodriguez2006,
    author = {Juan J. Rodriguez and Ludmila I. Kuncheva and Carlos J. Alonso},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    number = {10},
    pages = {1619-1630},
    title = {Rotation Forest: A new classifier ensemble method},
    volume = {28},
    year = {2006},
    ISSN = {0162-8828},
    URL = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211}
 }

    Valid options are: 

     -N
  Whether minGroup (-G) and maxGroup (-H) refer to
  the number of groups or their size.
  (default: false)
     -G <num>
  Minimum size of a group of attributes:
   if numberOfGroups is true, the minimum number
   of groups.
   (default: 3)
     -H <num>
  Maximum size of a group of attributes:
   if numberOfGroups is true, the maximum number
   of groups.
   (default: 3)
     -P <num>
  Percentage of instances to be removed.
   (default: 50)
     -F <filter specification>
  Full class name of filter to use, followed
  by filter options.
  eg: "weka.filters.unsupervised.attribute.PrincipalComponents-R 1.0"
     -S <num>
  Random number seed.
  (default 1)
     -I <num>
  Number of iterations.
  (default 10)
     -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.trees.J48)
     
 Options specific to classifier weka.classifiers.trees.J48:
 
     -U
  Use unpruned tree.
     -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)
     -M <minimum number of instances>
  Set minimum number of instances per leaf.
  (default 2)
     -R
  Use reduced error pruning.
     -N <number of folds>
  Set number of folds for reduced error
  pruning. One fold is used as pruning set.
  (default 3)
     -B
  Use binary splits only.
     -S
  Don't perform subtree raising.
     -L
  Do not clean up after the tree has been built.
     -A
  Laplace smoothing for predicted probabilities.
     -Q <seed>
  Seed for random data shuffling (default 1).
    Version:
    $Revision: 7012 $
    Author:
    Juan Jose Rodriguez (jjrodriguez@ubu.es)
    See Also:
    Serialized Form

    • Constructor Detail

      • RotationForest

        public RotationForest()
        Constructor.

    • 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

      • setOptions

        public void setOptions​(java.lang.String[] options)
                throws java.lang.Exception
        Parses a given list of options.

        Valid options are: 

         -N
  Whether minGroup (-G) and maxGroup (-H) refer to
  the number of groups or their size.
  (default: false)
         -G <num>
  Minimum size of a group of attributes:
   if numberOfGroups is true, the minimum number
   of groups.
   (default: 3)
         -H <num>
  Maximum size of a group of attributes:
   if numberOfGroups is true, the maximum number
   of groups.
   (default: 3)
         -P <num>
  Percentage of instances to be removed.
   (default: 50)
         -F <filter specification>
  Full class name of filter to use, followed
  by filter options.
  eg: "weka.filters.unsupervised.attribute.PrincipalComponents-R 1.0"
         -S <num>
  Random number seed.
  (default 1)
         -I <num>
  Number of iterations.
  (default 10)
         -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.trees.J48)
         
 Options specific to classifier weka.classifiers.trees.J48:
 
         -U
  Use unpruned tree.
         -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)
         -M <minimum number of instances>
  Set minimum number of instances per leaf.
  (default 2)
         -R
  Use reduced error pruning.
         -N <number of folds>
  Set number of folds for reduced error
  pruning. One fold is used as pruning set.
  (default 3)
         -B
  Use binary splits only.
         -S
  Don't perform subtree raising.
         -L
  Do not clean up after the tree has been built.
         -A
  Laplace smoothing for predicted probabilities.
         -Q <seed>
  Seed for random data shuffling (default 1).
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class RandomizableIteratedSingleClassifierEnhancer
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • numberOfGroupsTipText

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

      • setNumberOfGroups

        public void setNumberOfGroups​(boolean numberOfGroups)
        Set whether minGroup and maxGroup refer to the number of groups or their size
        Parameters:
        numberOfGroups - whether minGroup and maxGroup refer to the number of groups or their size

      • getNumberOfGroups

        public boolean getNumberOfGroups()
        Get whether minGroup and maxGroup refer to the number of groups or their size
        Returns:
        whether minGroup and maxGroup refer to the number of groups or their size

      • minGroupTipText

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

      • setMinGroup

        public void setMinGroup​(int minGroup)
                 throws java.lang.IllegalArgumentException
        Sets the minimum size of a group.
        Parameters:
        minGroup - the minimum value. of attributes.
        Throws:
        java.lang.IllegalArgumentException

      • getMinGroup

        public int getMinGroup()
        Gets the minimum size of a group.
        Returns:
        the minimum value.

      • maxGroupTipText

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

      • setMaxGroup

        public void setMaxGroup​(int maxGroup)
                 throws java.lang.IllegalArgumentException
        Sets the maximum size of a group.
        Parameters:
        maxGroup - the maximum value. of attributes.
        Throws:
        java.lang.IllegalArgumentException

      • getMaxGroup

        public int getMaxGroup()
        Gets the maximum size of a group.
        Returns:
        the maximum value.

      • removedPercentageTipText

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

      • setRemovedPercentage

        public void setRemovedPercentage​(int removedPercentage)
                          throws java.lang.IllegalArgumentException
        Sets the percentage of instance to be removed
        Parameters:
        removedPercentage - the percentage.
        Throws:
        java.lang.IllegalArgumentException

      • getRemovedPercentage

        public int getRemovedPercentage()
        Gets the percentage of instances to be removed
        Returns:
        the percentage.

      • projectionFilterTipText

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

      • setProjectionFilter

        public void setProjectionFilter​(Filter projectionFilter)
        Sets the filter used to project the data.
        Parameters:
        projectionFilter - the filter.

      • getProjectionFilter

        public Filter getProjectionFilter()
        Gets the filter used to project the data.
        Returns:
        the filter.

      • toString

        public java.lang.String toString()
        Returns description of the Rotation Forest classifier.
        Overrides:
        toString in class java.lang.Object
        Returns:
        description of the Rotation Forest classifier as a string

      • buildClassifier

        public void buildClassifier​(Instances data)
                     throws java.lang.Exception
        builds the classifier.
        Overrides:
        buildClassifier in class IteratedSingleClassifierEnhancer
        Parameters:
        data - the training data to be used for generating the classifier.
        Throws:
        java.lang.Exception - if the classifier could not be built successfully

      • distributionForInstance

        public double[] distributionForInstance​(Instance instance)
                                 throws java.lang.Exception
        Calculates the class membership probabilities for the given test instance.
        Overrides:
        distributionForInstance in class Classifier
        Parameters:
        instance - the instance to be classified
        Returns:
        preedicted class probability distribution
        Throws:
        java.lang.Exception - if distribution can't be computed successfully

      • main

        public static void main​(java.lang.String[] argv)
        Main method for testing this class.
        Parameters:
        argv - the options