… Fortunately, we find that although the three regions are all non-monotonic with respect to
the set inclusion of attributes, there exists a "monotonic ingredient" closely related to the three …

… Attribute reduction plays an important role in the areas of rough sets and granular computing…
If the amalgamation of the measures is non-monotonic, we may have L ( E A 1 , T ) ≥ L ( E A …

… to design related reduction algorithm. To address this problem, we propose a multi-objective
attribute reduction method based on NSGA-II for decision-theoretic rough set model. Three …

… rough set model can deal with numerical data directly. … attribute reduction in fuzzy
decision-theoretic rough set model, we propose two attribute reduction approaches: global reduction …

… [12] introduced a non-monotonic attribute reduction for decision-theoretic … “non-decreasing”
principle, we define attribute reduction in utility-based decision-theoretic rough set model as …

… rough set model and probabilistic rough set models can be derived from the decision-theoretic
rough set … For example, we can obtain the Pawlak rough set model if α = 1 and β = 0 , the …

… [10] investigated the non-monotonic attribute reduction issue in decision-theoretic … As we
discussed in Section 2, the decision-theoretic rough set is a successful rough set theory when …

… Decision-theoretic rough sets (DTRS), … Decision-Theoretic Rough Sets based on Evidence
Theory (GDTRSET) is put forward in this paper. The proposed GDTRSET extends the set of …

… attribute reducts. Based on the semantics of the three-way decisions, we introduce a monotonic
result cost in decision-theoretic rough set … classification-based attribute reducts from result…

… constant in order, \(\mu _N\) is non-monotonic decreasing with the increase in \(\mu _M(\…
\) is constant, \(\nu _N\) is non-monotonic decreasing with the increase in \(\nu _M(\lambda _…