Hierarchical Partitioning of the Output Space in Multi-label Data

no code implementations • 19 Dec 2016 • Yannis Papanikolaou, Ioannis Katakis, Grigorios Tsoumakas

Hierarchy Of Multi-label classifiers (HOMER) is a multi-label learning algorithm that breaks the initial learning task to several, easier sub-tasks by first constructing a hierarchy of labels from a given label set and secondly employing a given base multi-label classifier (MLC) to the resulting sub-problems.

Clustering Multi-Label Classification +1