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- W1968320134 abstract "This paper proposes LCSE, a learning classifier system ensemble, which is an extension of the classical learning classifier system(LCS). The classical LCS includes two major modules, a genetic algorithm module used to facilitate rule discovery, and a reinforcement learning module used to adjust the strength of the corresponding rules while it receives the rewards from the environment. In LCSE we build a two-level ensemble architecture to enhance the generalization of LCS. In the first-level, new instances are first bootstrapped and sent to several LCSs for classification. Then, in the second-level, a plurality-vote method is used to combine the classification results of individual LCSs into a final decision. Experiments on some benchmark data sets from the UCI repository have shown that LCSE has better generalization ability than the single LCS and other supervised learning methods." @default.
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- W1968320134 date "2005-06-25" @default.
- W1968320134 modified "2023-10-04" @default.
- W1968320134 title "Learning classifier system ensemble for data mining" @default.
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- W1968320134 doi "https://doi.org/10.1145/1102256.1102268" @default.
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