ICAS: An Incremental Concept Acquisition System Using Attribute-Based Description
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Abstract
ICAS is an incremental concept acquisition system using attribute-based description. It includes an algorithm for learning concept, which induces a rule set from an example set based on the probability theory, and an algorithm for refining the rule set. This paper also introduces the learning cycles, a very useful idea of ICAS. In fact, concept acquisition by ICAS is an incremental process consisting of many such learning cycles. Also the design and implementation of ICAS are given.
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