Abstract
An algorithm developed to help an expert generate rules is presented. The algorithm, which has been called RuLess, consists of two main stages: (i) a session to incrementally capture the rules, and (ii) a mechanism to simplify the rules. In general, it can be used on environments where there is a finite set of possible examples which are not available in advance, and from which a set of classification rules needs to be produced. It is useful in domains in which all the attributes are discrete and the number of examples is not too large, as the user needs to manually classify all the examples. RuLess was used to generate the tutoring rules of LacePro, a multifunctional system to learn, apply and consult established procedures. Based on the rules obtained for LacePro, the RuLess method was compared against the CN2 and Ripple Down Rules methods, which are two well-known rule generation procedures.
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© 2000 Springer-Verlag Berlin Heidelberg
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de Buen Rodriguez, P.R., Morales, E.F., Vadera, S. (2000). RuLess: A Method for the Acquisition and Simplification of Rules. In: Cairó, O., Sucar, L.E., Cantu, F.J. (eds) MICAI 2000: Advances in Artificial Intelligence. MICAI 2000. Lecture Notes in Computer Science(), vol 1793. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10720076_25
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DOI: https://doi.org/10.1007/10720076_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67354-5
Online ISBN: 978-3-540-45562-2
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