MODL: A Bayes optimal discretization method for continuous attributes
نویسندگان
چکیده
منابع مشابه
Optimal Multiple Intervals Discretization of Continuous Attributes for Supervised Learning
5, av Pierre Mend&s-France 69676 BRON CEDEX FRANCE {zighed,rakotoma,ffeschet)@univ-lyon2.fr In this paper, we propose an extension of Fischer’s algorithm to compute the optimal discretization of a continuous variable in the context of supervised learning. Our algorithm is extremely performant since its only depends on the number of runs and not directly on the number of points of the sample dat...
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In the data-mining field, many learning methods — such as association rules, Bayesian networks, and induction rules (Grzymala-Busse & Stefanowski, 2001) — can handle only discrete attributes. Therefore, before the machine-learning process, it is necessary to re-encode each continuous attribute in a discrete attribute constituted by a set of intervals. For example, the age attribute can be trans...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2006
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-006-8364-x