Abstract
In this paper we focus our attention on the classification problem. We use rough set theory and propose new methods for induction of decision rules. Our approach generalize the concept of a reduct in a dataset. We use minimal set of descriptors gained from decision table. A reduct of descriptors is a set of descriptors which allows us to distinguish between objects as well as the whole set of descriptors present in the dataset. Two types of descriptors are considered: attribute-value and attribute-object-value. We propose appropriate methodology for dealing with descriptors and inducing decision rules. We also present performed experiments on different datasets and compare them with results obtained by other algorithms for object classification based on rough sets.
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Dominik, A., Walczak, Z. (2006). Induction of Decision Rules Using Minimum Set of Descriptors. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_54
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DOI: https://doi.org/10.1007/11785231_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35748-3
Online ISBN: 978-3-540-35750-6
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