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Approximation reduction in inconsistent incomplete decision tables

delete2010-07-01
delete122
PRE
AI
Y
Yuhua Qian
J
Jiye Liang *
D
Deyu Li
N
Nannan Ma
DOI:10.1016/j.knosys.2010.02.004delete
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Abstract

Abstract

En 中文
This article deals with approaches to attribute reductions in inconsistent incomplete decision table. The main objective of this study is to extend a kind of attribute reductions called a lower approximation reduct and an upper approximation reduct, which preserve the lower/upper approximation distribution of a target decision. Several judgement theorems of a lower/upper approximation consistent set in inconsistent incomplete decision table are educed. Then, the discernibility matrices associated with the two approximation reductions are examined as well, from which we can obtain approaches to attribute reduction of an incomplete decision table in rough set theory. (C) 2010 Elsevier B.V. All rights reserved.
Keywords:
Rough set theory
Inconsistent incomplete decision table
Maximal consistent block
Discernibility function
Approximation reduction
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.2W
Citations:
4.5W

Organization

S
Shanxi University
Scholars:
1.3W
Papers: 8.4K
Citations: 1.2W