Documentation of 'weka.classifiers.meta.Vote' Java class
Vote
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weka.classifiers.meta

Class Vote

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, Classifier, Aggregateable<Classifier>, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, EnvironmentHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler

    public class Vote
extends RandomizableMultipleClassifiersCombiner
implements TechnicalInformationHandler, EnvironmentHandler, Aggregateable<Classifier>
    Class for combining classifiers. Different combinations of probability estimates for classification are available.

    For more information see:

    Ludmila I. Kuncheva (2004). Combining Pattern Classifiers: Methods and Algorithms. John Wiley and Sons, Inc..

    J. Kittler, M. Hatef, Robert P.W. Duin, J. Matas (1998). On combining classifiers. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(3):226-239.

    Valid options are: 

     -P <path to serialized classifier>
  Full path to serialized classifier to include.
  May be specified multiple times to include
  multiple serialized classifiers. Note: it does
  not make sense to use pre-built classifiers in
  a cross-validation.
 
     -R <AVG|PROD|MAJ|MIN|MAX|MED>
  The combination rule to use
  (default: AVG)
 
     -print
  Print the individual models in the output
 
     -S <num>
  Random number seed.
  (default 1)
 
     -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")
 
     -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
 
     -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
 
     Options specific to classifier weka.classifiers.rules.ZeroR:
 
     -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
 
     -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
    BibTeX: 
     @book{Kuncheva2004,
    author = {Ludmila I. Kuncheva},
    publisher = {John Wiley and Sons, Inc.},
    title = {Combining Pattern Classifiers: Methods and Algorithms},
    year = {2004}
 }
 
 @article{Kittler1998,
    author = {J. Kittler and M. Hatef and Robert P.W. Duin and J. Matas},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    number = {3},
    pages = {226-239},
    title = {On combining classifiers},
    volume = {20},
    year = {1998}
 }

    See Also:
    Serialized Form

    • Field Detail

      • AVERAGE_RULE

        public static final int AVERAGE_RULE
        combination rule: Average of Probabilities
        See Also:
        Constant Field Values

      • PRODUCT_RULE

        public static final int PRODUCT_RULE
        combination rule: Product of Probabilities (only nominal classes)
        See Also:
        Constant Field Values

      • MAJORITY_VOTING_RULE

        public static final int MAJORITY_VOTING_RULE
        combination rule: Majority Voting (only nominal classes)
        See Also:
        Constant Field Values

      • MIN_RULE

        public static final int MIN_RULE
        combination rule: Minimum Probability
        See Also:
        Constant Field Values

      • MAX_RULE

        public static final int MAX_RULE
        combination rule: Maximum Probability
        See Also:
        Constant Field Values

      • MEDIAN_RULE

        public static final int MEDIAN_RULE
        combination rule: Median Probability (only numeric class)
        See Also:
        Constant Field Values

      • TAGS_RULES

        public static final Tag[] TAGS_RULES
        combination rules

    • Constructor Detail

      • Vote

        public Vote()

    • Method Detail

      • globalInfo

        public java.lang.String globalInfo()
        Returns a string describing classifier
        Returns:
        a description suitable for displaying in the explorer/experimenter gui

      • setOptions

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

        Valid options are: 

         -P <path to serialized classifier>
  Full path to serialized classifier to include.
  May be specified multiple times to include
  multiple serialized classifiers. Note: it does
  not make sense to use pre-built classifiers in
  a cross-validation.
 
         -R <AVG|PROD|MAJ|MIN|MAX|MED>
  The combination rule to use
  (default: AVG)
 
         -print
  Print the individual models in the output
 
         -S <num>
  Random number seed.
  (default 1)
 
         -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")
 
         -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
 
         -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
 
         Options specific to classifier weka.classifiers.rules.ZeroR:
 
         -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
 
         -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
        Specified by:
        setOptions in interface OptionHandler
        Overrides:
        setOptions in class RandomizableMultipleClassifiersCombiner
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • 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

      • buildClassifier

        public void buildClassifier(Instances data)
                     throws java.lang.Exception
        Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
        Specified by:
        buildClassifier in interface Classifier
        Parameters:
        data - the training data to be used for generating the boosted classifier.
        Throws:
        java.lang.Exception - if the classifier could not be built successfully

      • addPreBuiltClassifier

        public void addPreBuiltClassifier(Classifier c)
        Add a prebuilt classifier to the list for use in the ensemble
        Parameters:
        c - a prebuilt Classifier to add.

      • removePreBuiltClassifier

        public void removePreBuiltClassifier(Classifier c)
        Remove a prebuilt classifier from the list to use in the ensemble
        Parameters:
        c - the classifier to remove

      • classifyInstance

        public double classifyInstance(Instance instance)
                        throws java.lang.Exception
        Classifies the given test instance.
        Specified by:
        classifyInstance in interface Classifier
        Overrides:
        classifyInstance in class AbstractClassifier
        Parameters:
        instance - the instance to be classified
        Returns:
        the predicted most likely class for the instance or Utils.missingValue() if no prediction is made
        Throws:
        java.lang.Exception - if an error occurred during the prediction

      • distributionForInstance

        public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception
        Classifies a given instance using the selected combination rule.
        Specified by:
        distributionForInstance in interface Classifier
        Overrides:
        distributionForInstance in class AbstractClassifier
        Parameters:
        instance - the instance to be classified
        Returns:
        the distribution
        Throws:
        java.lang.Exception - if instance could not be classified successfully

      • combinationRuleTipText

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

      • getCombinationRule

        public SelectedTag getCombinationRule()
        Gets the combination rule used
        Returns:
        the combination rule used

      • setCombinationRule

        public void setCombinationRule(SelectedTag newRule)
        Sets the combination rule to use. Values other than
        Parameters:
        newRule - the combination rule method to use

      • preBuiltClassifiersTipText

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

      • setPreBuiltClassifiers

        public void setPreBuiltClassifiers(java.io.File[] preBuilt)
        Set the paths to pre-built serialized classifiers to load and include in the ensemble
        Parameters:
        preBuilt - an array of File paths to serialized models

      • getPreBuiltClassifiers

        public java.io.File[] getPreBuiltClassifiers()
        Get the paths to pre-built serialized classifiers to load and include in the ensemble
        Returns:
        an array of File paths to serialized models

      • doNotPrintModelsTipText

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

      • setDoNotPrintModels

        public void setDoNotPrintModels(boolean print)
        Set whether to print the individual ensemble models in the output
        Parameters:
        print - true if the individual models are to be printed

      • getDoNotPrintModels

        public boolean getDoNotPrintModels()
        Get whether to print the individual ensemble models in the output
        Returns:
        true if the individual models are to be printed

      • toString

        public java.lang.String toString()
        Output a representation of this classifier
        Overrides:
        toString in class java.lang.Object
        Returns:
        a string representation of the classifier

      • setEnvironment

        public void setEnvironment(Environment env)
        Set environment variable values to substitute in the paths of serialized models to load
        Specified by:
        setEnvironment in interface EnvironmentHandler
        Parameters:
        env - the environment variables to use

      • aggregate

        public Classifier aggregate(Classifier toAggregate)
                     throws java.lang.Exception
        Aggregate an object with this one
        Specified by:
        aggregate in interface Aggregateable<Classifier>
        Parameters:
        toAggregate - the object to aggregate
        Returns:
        the result of aggregation
        Throws:
        java.lang.Exception - if the supplied object can't be aggregated for some reason

      • finalizeAggregation

        public void finalizeAggregation()
                         throws java.lang.Exception
        Call to complete the aggregation process. Allows implementers to do any final processing based on how many objects were aggregated.
        Specified by:
        finalizeAggregation in interface Aggregateable<Classifier>
        Throws:
        java.lang.Exception - if the aggregation can't be finalized for some reason

      • 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]
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