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A Variable Precision Rough Set Model for Interval data  

Kim, Kyeong-Taek (Dept. of Industrial and Management Engineering, Hannam University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.34, no.2, 2011 , pp. 30-34 More about this Journal
Abstract
Variable precision rough set models have been successfully applied to problems whose domains are discrete values. However, there are many situations where discrete data is not available. When it comes to the problems with interval values, no variable precision rough set model has been proposed. In this paper, we propose a variable precision rough set model for interval values in which classification errors are allowed in determining if two intervals are same. To build the model, we define equivalence class, upper approximation, lower approximation, and boundary region. Then, we check if each of 11 characteristics on approximation that works in Pawlak's rough set model is valid for the proposed model or not.
Keywords
Variable Precision Rough Set Model; Interval Values; Classification Error;
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