We generalize the notion of an approximation space introduced in [8]. In tolerance
approximation spaces we define the lower and upper set approximations. We investigate …

The rough set theory, based on the conventional indiscernibility relation, is not useful for
analysing incomplete information. We introduce two generalizations of this theory. The first …

Since Pawlak [43] proposed the rough set theory in early eighties, many proposals have
been made for generalizing and interpreting rough sets [3, 4, 19, 27, 37, 38, 39, 46, 47, 51 …

The paper explores the concepts of approximate relations and functions in the framework of
the theory of rough sets. The difficulties with the application of the idea of rough relation to …

RT (Pn). So, RB (Pn)⊆ RT (Pn). Moreover, RB (P) is symmetric by definition, for any pre-
topology P. Hence it is a tolerance relation, because reflexivity is inherited by the pre …

Page 1 Studies in Computational Intelligence 152 S Jarosław Stepaniuk Rough - Granular
Computing in Knowledge Discovery and Data Mining R43 563 0404 R437 R438 Springer …

The amount of electronic data available is growing very fast and this explosive growth in
databases has generated a need for new techniques and tools that can intelligently and …

Approximation Spaces were introduced in order to analyse data on the basis of
Indiscernibility Spaces, that is, spaces of the form< U, E>, where U is a universe of items and …

This chapter addresses issues concerning a problem of constructing an optimal
classification algorithm. The notion of a parameterized approximation space is used to …

A systematic procedure for deriving weakly ordered non-numerical rankings from given sets
of data is proposed and analysed. The data are assumed to be collected using the Pairwise …