Uncertainty and feature selection in rough set theory

Authors:
Jiye Liang
Affiliations:
Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, School of Computer and Information Technology, 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

In rough set theory, the uncertainty of granulation and efficient feature selection algorithms have attracted much attention in recent years. We focus on the review of several common uncertainty measures and the relationships among them. An efficient accelerator is developed to accelerate a heuristic process of feature selection.