After probability theory, fuzzy set theory and evidence theory, rough set theory is a new
mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge …

Probabilistic approaches have been applied to the theory of rough set in several forms,
including decision-theoretic analysis, variable precision analysis, and information-theoretic …

Many previous studies on face recognition attempted to seek a precise classifier to achieve
a low misclassification error, which is based on an assumption that all misclassification costs …

Three-way decisions provide a means for trading off different types of classification error in
order to obtain a minimum cost ternary classifier. This paper compares probabilistic three …

The original rough set model was developed by Pawlak, which is mainly concerned with the
approximation of sets described by a single binary relation on the universe. In the view of …

Worldwide, there has been a rapid growth in interest in rough set theory and its applications
in recent years. Evidence of this can be found in the increasing number of high-quality …

As a natural extension of three-way decisions with incomplete information, this paper
provides a novel three-way decision model based on incomplete information system. First …

The Bayesian decision-theoretic rough sets propose a framework for studying rough set
approximations using probabilistic theory, which can interprete the parameters from existing …

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The original rough-set model is primarily concerned with the approximations of sets
described by a single equivalence relation on a given universe. With granular computing …