JACIII Vol.15 No.1 pp. 110-116
doi: 10.20965/jaciii.2011.p0110


Variable Precision Rough Set Model in Information Tables with Missing Values

Yoshifumi Kusunoki and Masahiro Inuiguchi

Department of Systems Innovation, Graduate School of Engineering Sciences, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan

March 9, 2010
April 22, 2010
January 20, 2011
rough sets, missing values, variable precision rough set model, lower and upper rough membership functions
In this paper, we study rough set models in information tables with missing values. The variable precision rough set model proposed by Ziarko tolerates misclassification error using a membership function in complete information tables. We generalize the variable precision rough set in information tables with missing values. Because of incompleteness, the membership degree of each objects becomes an interval value. We define six different approximate regions using the lower and upper bounds of membership functions. The properties of the proposed rough set model are investigated. Moreover we show that the proposed model is a generalization of rough set models based on similarity relations.
Cite this article as:
Y. Kusunoki and M. Inuiguchi, “Variable Precision Rough Set Model in Information Tables with Missing Values,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.1, pp. 110-116, 2011.
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