2006 | OriginalPaper | Buchkapitel
Hypothesis Diversity in Ensemble Classification
verfasst von : Lorenza Saitta
Erschienen in: Foundations of Intelligent Systems
Verlag: Springer Berlin Heidelberg
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The paper discusses the issue of hypothesis diversity in ensemble classifiers. The measures of diversity previously proposed in the literature are analyzed inside a unifying framework based on Monte Carlo stochastic algorithms. The paper shows that no measure is useful to predict ensemble performance, because all of them have only a very loose relation with the expected accuracy of the classifier.