標題: Variable Precision Fuzzy Rough Set Based on Relative Cardinality
作者: Fan, Tuan-Fang
Liau, Churn-Jung
Liu, Duen-Ren
資訊管理與財務金融系
註:原資管所+財金所

Department of Information Management and Finance
關鍵字: fuzzy set;rough set;variable precision rough set;fuzzy cardinality
公開日期: 2012
摘要: The fuzzy rough set approach (FRSA) is a theoretical framework that can deal with data analysis of possibilistic information systems. While a set of comprehensive rules can be induced from a possibilistic information system by using FRSA, generation of several intuitively justified rules is sometimes blocked by objects that only partially satisfy the antecedents of the rules. In this paper, we use the variable precision models of FRSA to cope with the problem. The models admit rules that are not satisfied by all objects. It is only required that the proportion of objects satisfying the rules must be above a threshold called a a precision level. In the presented models, the proportion of objects is represented as a relative cardinality of a fuzzy set with respect to another fuzzy set. We investigate three types of models based on different definitions of fuzzy cardinalities including Sigma-counts, possibilistic cardinalities, and probabilistic cardinalities; and the precision levels corresponding to the three types of models are respectively scalars, fuzzy numbers, and random variables.
URI: http://hdl.handle.net/11536/135473
ISBN: 978-83-60810-48-4
期刊: 2012 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS)
起始頁: 43
結束頁: 47
顯示於類別:會議論文