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Rules as attributes in classifier construction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (1999) 1711 492-499
DOI: 10.1007/978-3-540-48061-7_60
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Abstract

A method for constructing classification (decision) systems is presented. The use of decision rules derived using rough set methods as new attributes is considered. Neural networks are applied as a tool for construction of classifier over reconstructed dataset. Possible profits of such an approach are briey presented together with results of preliminary experiments.

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Szczuka, M. S. (1999). Rules as attributes in classifier construction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1711, pp. 492–499). Springer Verlag. https://doi.org/10.1007/978-3-540-48061-7_60

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