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- W2106016552 abstract "In this paper, we focus on expert knowledge incorporation in supervised learning tasks particularly decision rules. We aim to improve their quality, reduce their number and increase their prediction's rate. The proposed method consists of initially applying Knowledge Discovery in Databases process (KDD) on a database relating to Echinoderms. It aims to improve then classification rules' performance using background knowledge. This method is evaluated on a real domain area concerning Echinoderms. Experimental results are relevant; they generally improve performance and reduce prediction rules number." @default.
- W2106016552 created "2016-06-24" @default.
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- W2106016552 date "2013-05-01" @default.
- W2106016552 modified "2023-09-28" @default.
- W2106016552 title "Expert knowledge and supervised learning of rules: Application to Echinoderms" @default.
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- W2106016552 doi "https://doi.org/10.1109/codit.2013.6689561" @default.
- W2106016552 hasPublicationYear "2013" @default.
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