Complexity of learning in concept lattices from positive and negative examples
نویسنده
چکیده
A model of learning from positive and negative examples in concept lattices is considered. Latticeand graph-theoretic interpretations of learning concept-based classi0cation rules (called hypotheses) and classi0cation in this model are given. The problems of counting all formal concepts, all hypotheses, and all minimal hypotheses are shown to be #P-complete. NP-completeness of some decision problems related to learning and classi0cation in this setting is demonstrated and several conditions of tractability of these problems are considered. Some useful particular cases where these problems can be solved in polynomial time are indicated. c © 2004 Elsevier B.V. All rights reserved.
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ورودعنوان ژورنال:
- Discrete Applied Mathematics
دوره 142 شماره
صفحات -
تاریخ انتشار 2004