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- W1858553808 abstract "In the field of pattern recognition, the concept of multiple classifier systems (MCS) was proposed as a method for the development of high-performance classification systems. At present, the common operation mechanism of MCS is the combination of classifier outputs. Recently, some researchers have pointed out the potentialities of dynamic classifier selection as a new operation mechanism. In a previous paper, the authors discussed the advantages of selection-based MCS and proposed an algorithm for dynamic classifier selection. In this paper, a theoretical framework for dynamic classifier selection is described and two methods for selecting classifiers are proposed. Reported results on the classification of different data sets show that dynamic classifier selection is an effective method for the development of MCS." @default.
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- W1858553808 date "2003-01-20" @default.
- W1858553808 modified "2023-09-27" @default.
- W1858553808 title "Methods for dynamic classifier selection" @default.
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- W1858553808 doi "https://doi.org/10.1109/iciap.1999.797670" @default.
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