In the Pawlak rough set model, the positive region, the boundary region and the non-
negative region are monotonic with respect to the set inclusion of attributes. However, the …

For most attribute reduction in Pawlak rough set model (PRS), monotonicity is a basic
property for the quantitative measure of an attribute set. Based on the monotonicity, a series …

In classical rough set models, attribute reduction generally keeps the positive or non-
negative regions unchanged, as these regions do not decrease with the addition of …

The monotonicity of positive region in PRS (Pawlak Rough Set) and DTRS (Decision-
Theoretic Rough Set) are comparatively discussed in this paper. Theoretic analysis shows …

This paper studies the definitions of attribute reduction in the decision-theoretic rough set
model, which focuses on the probabilistic regions that induce different types of decision …

This paper considers two groups of studies on attribute reduction in the decision-theoretic
rough set model. Attribute reduction can be interpreted based on either decision …

Decision-theoretic rough set model can derive several probabilistic rough set models by
providing proper cost functions. Learning cost functions from data automatically is the key to …

Cost sensitivity is an important problem, which has been addressed by many researchers
around the world. As far as cost sensitivity in the rough set theory is concerned, two types of …

Decision-theoretic rough set model, as a probabilistic generalization of the Pawlak rough set
model, is an effective method for decision making from vague, uncertain or imprecise data …

The variable precision rough set model resists noise in data by introducing a parameter to
relax the strict inclusion in approximations of the classical rough set model, and attribute …