An efficient fuzzy-rough attribute reduction approach

Authors:
Yuhua Qian;Chao Li;Jiye Liang
Affiliations:
Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, Shanxi, China;Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, Shanxi, China;Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, Shanxi, China
Venue:
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Year:
2011

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Abstract

Fuzzy rough set method provides an effective approach to data mining and knowledge discovery from hybrid data including categorical values and numerical values. However, its time-consumption is very intolerable to analyze data sets with large scale and high dimensionality. In this paper, we propose a strategy to improve a heuristic process of fuzzy-rough feature selection. Experiments show that this modified algorithm is much faster than its original version. It is worth noting that the performance of the modified algorithm becomes more visible when dealing with larger data sets.