EXTRACTING LAWS FROM DECISION TABLES: A ROUGH SET APPROACH |
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| Authors: | A Skowron |
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| Affiliation: | Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warsaw, Poland |
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| Abstract: | We present some methods, based on the rough set and Boolean reasoning approaches, for extracting laws from decision tables. First we discuss several procedures for decision rules synthesis from decision tables. Next we show how to apply some near-to-functional relations between data to data filtration. Two methods of searching for new classifiers (features) are described: searching for new classifiers in a given set of logical formulas, and searching for some functions approximating near-to-functional relations. |
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| Keywords: | reasoning under uncertainty rough sets knowledge discovery machine learning |
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