A novel rough set approach is proposed in this paper to discover classification rules through
a process of knowledge induction which selects decision rules with a minimal set of features …

Set-valued ordered information systems can be classified into two categories: disjunctive
and conjunctive systems. Through introducing two new dominance relations to set-valued …

Approximations of a concept by a variable precision rough-set model (VPRS) usually vary
under a dynamic information system environment. It is thus effective to carry out incremental …

Multigranulation rough set is an expansion of the classical rough set by using multiple
granular structures. Presently, three important multigranulation rough sets have been …

A few of clustering techniques for categorical data exist to group objects having similar
characteristics. Some are able to handle uncertainty in the clustering process while others …

Human beings often observe objects or deal with data hierarchically structured at different
levels of granulations. In this paper, we study optimal scale selection in multi-scale decision …

The probabilistic rough set (PRS) model, through the incorporation of error levels,
represents a quantitative extension of the classical rough set model. It serves as a …

In terms of neighborhood rough sets, the tri-level granular structure of neighborhood system
(carrying the neighborhood granule, swarm, and library) establishes a granular computing …

A granular structure of intuitionistic fuzzy (IF) information presents simultaneously the
similarity and diversity of samples. However, this structural representation has rarely …

Interval information systems are generalized models of single-valued information systems.
By introducing a dominance relation to interval information systems, we propose a ranking …