Abstract
Some combinatorical problems concerned with using rough set theory in knowledge discovery (KD) and data analysis can be successfully solved using genetic algorithms (GA) — a sophisticated, adaptive search method based on the Darwinian principle of natural selection (see [4], [6]). These problems are frequently NP-hard, as in case of reducts or templates finding (see [12]), and there is no fast and reliable way to solve them in deterministic way.
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Wróblewski, J. (1998). Genetic Algorithms in Decomposition and Classification Problems. In: Polkowski, L., Skowron, A. (eds) Rough Sets in Knowledge Discovery 2. Studies in Fuzziness and Soft Computing, vol 19. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1883-3_24
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DOI: https://doi.org/10.1007/978-3-7908-1883-3_24
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