B C D E G M N S T W

B

buildClassifier(Instances) - Method in class weka.classifiers.meta.END
Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Builds tree recursively.
buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Builds tree recursively.
buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Builds the classifier.
buildClassifierForNode(ND.NDTree, Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Builds the classifier for one node.

C

ClassBalancedND - Class in weka.classifiers.meta.nestedDichotomies
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
ClassBalancedND() - Constructor for class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Constructor.

D

DataNearBalancedND - Class in weka.classifiers.meta.nestedDichotomies
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random data-balanced tree structure.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
DataNearBalancedND() - Constructor for class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Constructor.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.END
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Predicts the class distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Predicts the class distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Predicts the class distribution for a given instance

E

END - Class in weka.classifiers.meta
A meta classifier for handling multi-class datasets with 2-class classifiers by building an ensemble of nested dichotomies.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
END() - Constructor for class weka.classifiers.meta.END
Constructor.

G

getCapabilities() - Method in class weka.classifiers.meta.END
Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.nestedDichotomies.ND
Returns default capabilities of the classifier.
getRevision() - Method in class weka.classifiers.meta.END
Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.nestedDichotomies.ND
Returns the revision string.
getString(int[]) - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Returns the list of indices as a string.
getString(int[]) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Returns the list of indices as a string.
getTechnicalInformation() - Method in class weka.classifiers.meta.END
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.
getTechnicalInformation() - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
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.
getTechnicalInformation() - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
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.
getTechnicalInformation() - Method in class weka.classifiers.meta.nestedDichotomies.ND
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.
globalInfo() - Method in class weka.classifiers.meta.END
Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
 
globalInfo() - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
 
globalInfo() - Method in class weka.classifiers.meta.nestedDichotomies.ND
 

M

main(String[]) - Static method in class weka.classifiers.meta.END
Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.nestedDichotomies.ND
Main method for testing this class.

N

ND - Class in weka.classifiers.meta.nestedDichotomies
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random tree structure.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
ND() - Constructor for class weka.classifiers.meta.nestedDichotomies.ND
Constructor.

S

setHashtable(Hashtable) - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Set hashtable from END.
setHashtable(Hashtable) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Set hashtable from END.
setHashtable(Hashtable) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Set hashtable from END.

T

toString() - Method in class weka.classifiers.meta.END
Returns description of the committee.
toString() - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Outputs the classifier as a string.
toString() - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Outputs the classifier as a string.
toString() - Method in class weka.classifiers.meta.nestedDichotomies.ND
Outputs the classifier as a string.

W

weka.classifiers.meta - package weka.classifiers.meta
 
weka.classifiers.meta.nestedDichotomies - package weka.classifiers.meta.nestedDichotomies
 

B C D E G M N S T W