The K-Nearest Neighbor search (kNN) problem has been investigated extensively in the past due to its broad range of applications. In this paper we study this problem in the contex...
This paper focuses on the application of rough set constructs to inductive learning from a database. A design guideline is suggested, which provides users the option to choose app...
This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...
In this paper we introduce the concept of valued tolerance as an extension of the usual concept of indiscernibility (which is a crisp equivalence relation) in rough sets theory. So...
A rough self-organizing map (RSOM) with fuzzy discretization of feature space is described here. Discernibility reducts obtained using rough set theory are used to extract domain k...