Systems for inducing concept descriptions from examples are valuable tools for assisting in the task of knowledge acquisition for expert systems. This paper presents a description and empirical evaluation of a new induction system, CN2, designed for the efficient induction of simple, comprehensible production rules in domains where problems of poor description language and/or noise may be present. Implementations of the CN2, ID3, and AQ algorithms are compared on three medical classification tasks. © 1989, Kluwer Academic Publishers. All rights reserved.
CITATION STYLE
Clark, P., & Niblett, T. (1989). The CN2 Induction Algorithm. Machine Learning, 3(4), 261–283. https://doi.org/10.1023/A:1022641700528
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