We present a general rule induction algorithm based on sequential covering, suitable for
variable consistency rough set approaches. This algorithm, called VC-DomLEM, can be …

This article investigates the Game-theoretic Rough Set (GTRS) model and its capability of
analyzing a major decision problem evident in existing probabilistic rough set models. A …

Attribute reduction is an important application of rough set theory. Most existing rough set
models do not consider the weight information of attributes in information systems. In this …

Feature selection is an important preprocessing step in machine learning and data mining.
In real-world applications, costs, including money, time and other resources, are required to …

In decision making processes, an expert with hesitant attitudes may experience difficulties
when evaluating alternatives via a single assessment value. By allowing the membership …

Multigranulation rough sets (MGRS) is one of desirable directions in rough set theory, in
which lower/upper approximations are approximated by granular structures induced by …

Multigranulation rough sets (MGRSs) where a target concept is approximated by granular
structures induced by multiple binary relations have been applied successfully in many …

The principle of the minority subordinate to the majority is the most feasible and credible
when people make decisions in real world. So generalized multigranulation rough set theory …

As a typical methodology to deal with uncertain issues, the three-way decision (3WD) has
been developed rapidly in nearly ten years, both in theories and applications. Three-way …

One of the strengths of rough set theory is the fact that an unknown target concept can be
approximately characterized by existing knowledge structures in a knowledge base …