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A reduct derived from feature selection
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AI
DOI：10.1016/j.patrec.2012.03.028.png)
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In this paper, the relationship between a selected subset of attribute set of a decision system via feature selection by an optimal algorithm and a reduct of attribute set under the meaning of Pawlak's rough set is discussed. This selected subset is considered as a solution of the optimal algorithm. It is verified that a locally optimal solution is surely not a reduct while a reduct must be a globally optimal solution. Based on these assertions, a new optimal algorithm, called blindly deleting algorithm with an inverse ordering (BDAIO), is proposed to find a real reduct of a decision information system by remedying the selected attribute subset. Several standard data sets from UCI repository are implemented showing validity of the proposal. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Attribute reduction
Feature selection
Decision systems
Rough sets
Data mining
期刊
IF:
3.3
论文数:
7.9K
被引数:
1.6W
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