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

The rough set theory approximates a concept by three regions, namely, the positive,
boundary and negative regions. Rules constructed from the three regions are associated …

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 …

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 …

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 …

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Decision-theoretic rough set models are a probabilistic extension of the algebraic rough set
model. The required parameters for defining probabilistic lower and upper approximations …

Rough set theory can be applied to rule induction. There are two different types of
classification rules, positive and boundary rules, leading to different decisions and …

The original Rough Set model is concerned primarily with algebraic properties of
approximately defined sets. The Variable Precision Rough Set (VPRS) model extends the …

Text of abstract Logistic regression analysis is an effective approach to the classification
problem. However, it may lead to high misclassification rate in real decision procedures …