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Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles
2007
Pattern Recognition Letters
One of the most important steps in the design of a multi-classifier system (MCS), also known as ensemble, is the choice of the components (classifiers). This step is very important to the overall performance of a MCS since the combination of a set of identical classifiers will not outperform the individual members. The ideal situation would be a set of classifiers with uncorrelated errors -they would be combined in such a way as to minimize the effect of these failures. This paper presents an
doi:10.1016/j.patrec.2006.09.001
fatcat:cmjypmogjbcefb3gemkotok4ii