The CN2 Induction Algorithm
作者:Peter Clark, Tim Niblett
摘要
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.
论文关键词:Concept learning, rule induction, noise, comprehensibility
论文评审过程:
论文官网地址:https://doi.org/10.1023/A:1022641700528