All Packages  Class Hierarchy  This Package  Previous  Next  Index  WEKA's home

Class weka.classifiers.meta.Vote 

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.meta.Vote
public class Vote
extends DistributionClassifier
implements OptionHandler
Class for combining classifiers using unweighted average (i.e. Voting) Valid options from the command line are:

-D
Turn on debugging output.

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a scheme included for selection followed by options to the classifier (required, option should be used once for each classifier).

Version:
$Revision: 1.1 $
Author:
Alexander K. Seewald (alex@seewald.at)

Constructor Index

o Vote()
 

Method Index

o buildClassifier(Instances)
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
o distributionForInstance(Instance)
Classifies a given instance using the selected classifier.
o getClassifier(int)
Gets a single classifier from the set of available classifiers.
o getClassifiers()
Gets the list of possible classifers to choose from.
o getDebug()
Get whether debugging is turned on
o getOptions()
Gets the current settings of the Classifier.
o getSeed()
Gets the random number seed.
o listOptions()
Returns an enumeration describing the available options
o main(String[])
Main method for testing this class.
o setClassifiers(Classifier[])
Sets the list of possible classifers to choose from.
o setDebug(boolean)
Set debugging mode
o setOptions(String[])
Parses a given list of options.
o setSeed(int)
Sets the seed for random number generation.
o toString()
Output a representation of this classifier

Constructor Detail

o Vote
public Vote()

Method Detail

o listOptions
public java.util.Enumeration listOptions()
          Returns an enumeration describing the available options
Returns:
an enumeration of all the available options
o setOptions
public void setOptions(java.lang.String options[]) throws java.lang.Exception
          Parses a given list of options. Valid options are:

-D
Turn on debugging output.

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a scheme included for selection followed by options to the classifier (required, option should be used once for each classifier).

Parameters:
options - the list of options as an array of strings
Throws:
java.lang.Exception - if an option is not supported
o getOptions
public java.lang.String[] getOptions()
          Gets the current settings of the Classifier.
Returns:
an array of strings suitable for passing to setOptions
o setClassifiers
public void setClassifiers(Classifier classifiers[])
          Sets the list of possible classifers to choose from.
Parameters:
classifiers - an array of classifiers with all options set.
o getClassifiers
public Classifier[] getClassifiers()
          Gets the list of possible classifers to choose from.
Returns:
the array of Classifiers
o getClassifier
public Classifier getClassifier(int index)
          Gets a single classifier from the set of available classifiers.
Parameters:
index - the index of the classifier wanted
Returns:
the Classifier
o setSeed
public void setSeed(int seed)
          Sets the seed for random number generation.
Parameters:
seed - the random number seed
o getSeed
public int getSeed()
          Gets the random number seed.
Returns:
the random number seed
o setDebug
public void setDebug(boolean debug)
          Set debugging mode
Parameters:
debug - true if debug output should be printed
o getDebug
public boolean getDebug()
          Get whether debugging is turned on
Returns:
true if debugging output is on
o 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.
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
Overrides:
buildClassifier in class Classifier
o distributionForInstance
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
          Classifies a given instance using the selected classifier.
Parameters:
instance - the instance to be classified
Throws:
java.lang.Exception - if instance could not be classified successfully
Overrides:
distributionForInstance in class DistributionClassifier
o toString
public java.lang.String toString()
          Output a representation of this classifier
Overrides:
toString in class java.lang.Object
o 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] 
All Packages  Class Hierarchy  This Package  Previous  Next  Index  WEKA's home