Package mulan.classifier.meta

Class Summary
ClusteringBased Class implementing clustering-based multi-label classification.
ConstrainedKMeans Cluster data using the constrained k means algorithm

ConstrainedKMeans.bucketInstance Class for representing an instance inside a bucket
EnsembleOfSubsetLearners A class for gathering several different SubsetLearners into a composite ensemble model.
HierarchyBuilder Class that builds a hierarchy on flat lables of given mulltilabel data.
HMC Class that implements a Hierarchical Multilabel classifier (HMC).
HMCNode Class that implements a node for the HMC
HOMER Class implementing the Hierarchy Of Multi-labEl leaRners algorithm.
MultiLabelMetaLearner Base class for multi-label learners, which use other multi-label learners
RAkEL Class implementing a generalized version of the RAkEL (RAndom k-labELsets) algorithm.
RAkELd Class implementing a generalized version of the RAkEL-d (RAndom k-labELsets) algorithm with disjoint labelsets.
SubsetLearner A class for learning a classifier according to disjoint label subsets: a multi-label learner (the Label Powerset by default) is applied to subsets with multiple labels and a single-label learner is applied to single label subsets.
 

Enum Summary
HierarchyBuilder.Method The different types of distributing labels to children nodes