Improved Variable Precision Rough Set Model and its Application to Distance Learning

Abstract

Improved Variable Precision Rough Set (VPRS) is proposed to extract the significant decision rules from a Student Information Table (SIT) in the distance learning environment. Moreover, two approaches are proposed. The first approach, VPRS based on Bayesian Confirmation Measures (BCM) is presented in order to handle totally ambiguous and enhance the precision of Rough set, and to deal with multi decision classes. The second approach, the VPRS parameters are refined, especially with multi decision classes. These concepts have been demonstrated by an example. The simulated result gives good accuracy and precise information with few computational steps.