2010 | OriginalPaper | Buchkapitel
Multi-information Ensemble Diversity
verfasst von : Zhi-Hua Zhou, Nan Li
Erschienen in: Multiple Classifier Systems
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Understanding ensemble diversity is one of the most important fundamental issues in ensemble learning. Inspired by a recent work trying to explain ensemble diversity from the information theoretic perspective, in this paper we study the ensemble diversity from the view of
multi-information
. We show that from this view, the ensemble diversity can be decomposed over the component classifiers constituting the ensemble. Based on this formulation, an approximation is given for estimating the diversity in practice. Experimental results show that our formulation and approximation are promising.