Variable precision fuzzy rough set based on relative cardinality

Tuan Fang Fan*, Churn Jung Liau, Duen-Ren Liu

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

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 Σ-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.

原文English
主出版物標題2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012
頁面43-47
頁數5
出版狀態Published - 1 十二月 2012
事件2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012 - Wroclaw, Poland
持續時間: 9 九月 201212 九月 2012

出版系列

名字2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012

Conference

Conference2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012
國家/地區Poland
城市Wroclaw
期間9/09/1212/09/12

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