期刊
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS
卷 39, 期 8, 页码 813-838出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/03081079.2010.499102
关键词
rough set theory; attribute reduction; decision performance evaluation; information entropy
资金
- National Natural Science Foundation of China [60773133, 70971080, 60903110]
- High Technology Research and Development Programme of China (863) [2007AA 01Z165]
- National Key Basic Research and Development Programme of China (973) [2007CB311002]
- Natural Science Foundation of Shanxi Province [2008011038, 009021017-1]
The given attribute reduction approach decides the decision performance of a reduced decision table, which can give a guidance for selecting one rule-extraction method in practical applications. The objective of this study is to compare the decision performance of positive-region reduction, Shannon entropy reduction and Liang entropy reduction. In this paper, the relationships between positive-region reduction, Shannon entropy reduction and Liang entropy reduction are first investigated. Then, by means of three evaluation indices (certainty measure, consistency measure and support measure), we systemically analyse these change mechanisms for decision performance of a decision table induced by each of these three types of reduction approaches. Finally, by numerical experiments, these change mechanisms of a decision table's decision performance are verified for the above-mentioned three attribute reductions.
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