ISSN:
0885-6125
Keywords:
Concept learning
;
rule induction
;
noise
;
comprehensibility
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract 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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1022641700528
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