Abstract
In this paper, the main techniques of inductive machine learning are united to the knowledge reduction theory based on rough sets from the theoretical point of view. And then the Monk’s problems are resolved again employing rough sets. As far as accuracy and conciseness are concerned, the learning algorithms based on rough sets have remarkable superiority to the previous methods.
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© 2003 Springer-Verlag Berlin Heidelberg
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Miao, D., Hou, L. (2003). An Application of Rough Sets to Monk’s Problems Solving. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_18
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DOI: https://doi.org/10.1007/3-540-39205-X_18
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