caa a22 4500 605468990 CHVBK 20210128100319.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1382-x doi (NATIONALLICENCE)springer-10.1007/s00500-014-1382-x Bidirectional heuristic attribute reduction based on conflict region [Elektronische Daten] [Hao Ge, Longshu Li, Yi Xu, Chuanjian Yang] Attribute reduction is one of the key issues in rough set theory. Many heuristic reduction strategies such as forward heuristic reduction, backward heuristic reduction and for-backward heuristic reduction have been proposed to obtain a subset of attributes which has the same discernibility as the original attribute set. However, some methods are usually computationally time consuming for large data sets. Therefore, this paper focuses on solving the attribute reduction efficiency in the decision system. We first introduce the quotient of approximation, positive region and conflict region, and then research the heuristic reduction algorithm based on conflict region. Sequentially, we put forward to a mechanism of bidirectional heuristic attribute reduction based on conflict region quotient and design a bidirectional heuristic attribute reduction algorithm. Finally, the experimental results with UCI data sets show that the proposed reduction algorithm is an effective technique to deal with large high-dimensional data sets. Springer-Verlag Berlin Heidelberg, 2014 Rough set theory nationallicence Attribute reduction nationallicence Positive region nationallicence Conflict region nationallicence Ge Hao Key Laboratory of Computation Intelligence and Signal Processing of Education Ministry, School of Computer Science and Technology, Anhui University, 230601, Hefei, People's Republic of China aut Li Longshu Key Laboratory of Computation Intelligence and Signal Processing of Education Ministry, School of Computer Science and Technology, Anhui University, 230601, Hefei, People's Republic of China aut Xu Yi Key Laboratory of Computation Intelligence and Signal Processing of Education Ministry, School of Computer Science and Technology, Anhui University, 230601, Hefei, People's Republic of China aut Yang Chuanjian School of Computer and Information Engineering, Chuzhou University, 239000, Chuzhou, People's Republic of China aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1973-1986 1432-7643 19:7<1973 2015 19 500 https://doi.org/10.1007/s00500-014-1382-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1382-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ge Hao Key Laboratory of Computation Intelligence and Signal Processing of Education Ministry, School of Computer Science and Technology, Anhui University, 230601, Hefei, People's Republic of China aut NATIONALLICENCE 700 1- Li Longshu Key Laboratory of Computation Intelligence and Signal Processing of Education Ministry, School of Computer Science and Technology, Anhui University, 230601, Hefei, People's Republic of China aut NATIONALLICENCE 700 1- Xu Yi Key Laboratory of Computation Intelligence and Signal Processing of Education Ministry, School of Computer Science and Technology, Anhui University, 230601, Hefei, People's Republic of China aut NATIONALLICENCE 700 1- Yang Chuanjian School of Computer and Information Engineering, Chuzhou University, 239000, Chuzhou, People's Republic of China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1973-1986 1432-7643 19:7<1973 2015 19 500