论文信息 - Concept learning by feature value interval abstraction

Concept learning by feature value interval abstraction

An approach to the machine learning of pattern classification rules (concepts) is described. Rules relating pattern classes to identifying responses are generated by generalizing examples of simple numerical patterns. Once a set of rules has been established, the concepts they embody may be described in symbolic form by mapping individual pattern classifications into a set of standard classes (developed from all the induced rules).Some of the limitations of the paradigm are discussed and a proposal is put forward for its enhancement.

D. J. H. Brown | D. J. Brown

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