期刊
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
卷 55, 期 1, 页码 259-274出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2013.04.011
关键词
Attribute reduction; Complexity reduction; Formal concept analysis; Rough set; Rules acquisition
资金
- Geographical Modeling and Geocomputation Program under the focused investment Scheme of The Chinese University of Hong Kong
- National Natural Science Foundation of China [60963006, 61173181, 61075120, 61272021]
- Humanities and Social Science funds Project of Ministry of Education of China [09YJCZH082, 11XJJAZH001]
- Zhejiang Provincial Natural Science Foundation of China [LZ12F03002]
- Science and Technology Project of Qingdao [12-1-4-4-(9)-jch]
In this paper, we introduce the notion of formal decision context as an extension of formal contexts by employing the notion of decision information table. We use formal concept analysis to formulate an approach to extract if-then rule from formal decision contexts. We also construct a knowledge-lossless method for complexity reduction in formal decision contexts so that the maximum rules extracted from the reduced formal decision contexts are identical to that extracted from the initial decision formal contexts. More specifically, we develop the discernibility matrix and the discernibility function in formal decision contexts to compute all of the attribute reductions without loss of knowledge. (C) 2013 Elsevier Inc. All rights reserved.
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