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Journals ACM SIGBIO Newsletter Volume 8 Issue 1

New methods for automated construction of knowledge bases for expert classification systems are being developed using a logic-based language and inductive inference techniques. This research addresses deficiencies of currently available methods for deriving classification rules from empiric data. Unate boolean functions are proposed as a useful language for logical classification rules. An example is given showing the use of an algorithm for converting unate functions to a "criteria table" knowledge representation.

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Automated learning of rules for heuristic classification systems

Spackman, A Kent
ACM SIGBIO Newsletter , Volume 8 (1)
Association for Computing Machinery – Mar 1, 1986

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