OPTIMIZATION PROBLEMS IN EXTENSION MATRIXES
摘要
In the extension matrix approach of inductive learning, the minimum formula (MFL) ofa positive example (e~+) against a set of negative examples (NE) and tbe optimal covering(MCV) of a set of positive examples (PE) against NE are two striking optimization prob-lems. They have been proved to be NP-hard in Ref. [1]. This paper presents four algorithms,named MFL, HFL, MCV and HCV respectively. Algorithms MFL and MCV are complete forsolving the problems MFL and MCV but they opelate in exponential time on the number ofattributes in an example space and polynomial time on the number of examples. AlgorithmsHFL and HCV are two heuristic algorithms homologous to Algorithms MFL and MCV buttheir time complexities are polynomial.
引用本文（GB/T 7714）
Xin Wu. OPTIMIZATION PROBLEMS IN EXTENSION MATRIXES[J]. 未知来源, 1992.
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