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• W51110959 abstract "Summary: In this chapter, we examine the trade-off between the size offuzzy rulebased systems and their classiification performance through computer simulations on commonly used data sets in the literature. The size of fuzzy systems (i.e., the number of fuzzy rules) depends on several factors such as input selection, fuzzy partition, and rule selection. First we illustrate the effect of the fuzzy partition of each input variable on the performance of fuzzy systems. Next we examine the effect of the input selection on the performance offuzzy systems through computer simulations using sequential feedforward input selection. The effect of the fuzzy partition is also examined in the same computer simulations. Finally, we directly examine a trade-off between the number of fuzzy rules and their classiifiication performance using a genetic algorithm-based fuzzy rule selection method with two objectives: to minimize the number of fuzzy rules and to maximize the classiification performance." @default.
• W51110959 created "2016-06-24" @default.
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• W51110959 date "2003-01-01" @default.
• W51110959 modified "2023-09-24" @default.
• W51110959 title "Trade-off between the Number of Fuzzy Rules and Their Classification Performance" @default.
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• W51110959 doi "https://doi.org/10.1007/978-3-540-37058-1_4" @default.
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