Attribute Reduction in the Bayesian Version of Variable Precision Rough Set Model
Dominik Ślȩzak, Wojciech Ziarko · Electronic Notes in Theoretical Computer Science · 2003
The article presents a parametric Bayesian extension of the rough set model, where the set approximations are defined by using the prior probability as a reference. It is shown that the quality of the Bayesian rough set models can be evaluated using probabilistic gain function which is suitable for easy computation of attribute reducts. It leads to the Bayesian style criteria for the attribute reduction within the rough set framework.