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