Journal Article10.1016/J.KNOSYS.2016.11.027
A general reduction algorithm for relation decision systems and its applications
Guilong Liu,Zheng Hua,Zehua Chen +2 more
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TL;DR: A new discernibility matrix is proposed to solve the attribute reduction problem for general relation decision systems and it is proposed that the results of classical attribute reduction approaches to be reinterpreted, giving them far greater unification and generality.
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Abstract: Give a general attribute reduction algorithm for relation decision systems.The algorithm unifies earlier positive region attribute reduction ones.Derive an algorithm for complete, incomplete and numerical decision tables.The reduction of covering decision systems is a special case of our algorithm. This paper studies the attribute reduction problem for general relation decision systems. We propose a new discernibility matrix to solve this problem. Combining the discernibility matrix and a recently proposed fast algorithm, we propose a simple and unified attribute reduction algorithm for relation decision systems that is not contingent on the consistency of relation decision systems. We derive the reduction algorithm for the special cases of complete, incomplete, and numerical decision tables. As an application, we transform the attribute reduction of relation decision systems into one for covering decision systems. This gives a convenient and effective reduction algorithm for covering decision systems. The reduction results obtained using University of California Irvine data sets show that the proposed algorithm is simple and efficient. Moreover, the proposed algorithm enables the results of classical attribute reduction approaches to be reinterpreted, giving them far greater unification and generality.
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Citations
Local attribute reductions for decision tables
Guilong Liu,Zheng Hua,Jiyang Zou +2 more
TL;DR: The concepts of lth decision class lower approximation reduction, lth decide class reduction, and lTh decision class β-reduction for decision tables are proposed, and their corresponding reduction algorithms via discernibility matrices are provided.
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A common attribute reduction form for information systems
TL;DR: A unified mathematical model of attribute Reduction by exactness for information systems is obtained, and it is shown that frequently used methods of attribute reduction for information system are exact.
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Attributes reduction algorithms for m-polar fuzzy relation decision systems
TL;DR: In this article , the authors present a systematic discussion of attribute reduction based on m-polar fuzzy (mF, in short) relation systems and mF relation decision systems.
25
Partial attribute reduction approaches to relation systems and their applications
Guilong Liu,Zheng Hua +1 more
TL;DR: This paper proposes the concepts of X -lower and -upper approximation reductions, and develops corresponding reduction algorithms for general relation systems, and derives lower and upper approximation reductions for relation decision systems.
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