Package meka.classifiers.multilabel.meta

Class Summary

Class	Description
BaggingML	BaggingML.java - Combining several multi-label classifiers using Bootstrap AGGregatING.
BaggingMLdup	BaggingMLdup.java - A version of BaggingML where Instances are duplicated instead of assigned higher weighs.
CM	CM.java - Classification Maximization using any multi-label classifier.
DeepML	DeepML.java - Deep Multi-label Classification.
EM	EM.java - Expectation Maximization using any multi-label classifier.
EnsembleML	EnsembleML.java - Combines several multi-label classifiers in a simple-subset ensemble.
FilteredClassifier	Allows the application of a filter in conjunction with a multi-label classifier.
MBR	MBR.java - Meta BR: BR stacked with feature outputs into another BR.
MetaProblemTransformationMethod	MultilabelMetaClassifier.java - For ensembles of multi-label methods.
RandomSubspaceML	RandomSubspaceML.java - Subsample the attribute space and instance space randomly for each ensemble member.
SubsetMapper	Maps the output of a multi-label classifier to a known label combination using the hamming distance.