A reduct derived from feature selection

Authors:
Tingquan Deng;Chengdong Yang;Xiaofei Wang
Affiliations:
College of Science, Harbin Engineering University, Harbin 150001, PR China and College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, PR China;College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, PR China and School of Informatics, Linyi University, Linyi 276100, PR China;College of Science, Harbin Engineering University, Harbin 150001, PR China
Venue:
Pattern Recognition Letters
Year:
2012

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Abstract

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.