- Full text PDF available (148)
- This year (3)
- Last 5 years (47)
- Last 10 years (95)
Journals and Conferences
Data Set Used
Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops, and international conferences in recent years. In… (More)
A rapid growth of interest in rough set theory  and its applications can be lately seen in the number of international workshops, conferences and seminars that are either directly dedicated to rough sets, include the subject in their programs, or simply accept papers that use this approach to solve problems at hand. A large number of high quality… (More)
In this article, we present some extensions of the rough set approach and we outline a challenge for the rough set based research. 2006 Elsevier Inc. All rights reserved.
We generalize the notion of an approximation space introduced in 8]. In tolerance approximation spaces we deene the lower and upper set approximations. We investigate some attribute reduction problems for tolerance approximation spaces determined by tolerance information systems. The tolerance relation deened by the so called uncertainty function or the… (More)
In this article, we discuss methods based on the combination of rough sets and Boolean reasoning with applications in pattern recognition, machine learning, data mining and conflict analysis. 2006 Elsevier Inc. All rights reserved.
s. The quantization of real value attributes is one of the main problem to be solved in synthesis of decision rules from data tables with real value attributes. We present an approach to this problem based on rough set methods and Boolean reasoning. The main result states that the problem of optimal quantization of real value attributes is polynomially… (More)
We present applications of rough set methods for feature selection in pattern recognition. We emphasize the role of the basic constructs of rough set approach in feature selection, namely reducts and their approximations, including dynamic reducts. In the overview of methods for feature selection we discuss feature selection criteria, including the rough… (More)
We are concerned with formal models of reasoning under uncertainty. Many approaches to this problem are known in the literature e.g. Dempster-Shafer theory, bayesian-based reasoning, belief networks, fuzzy logics etc. We propose rough mere-ology as a foundation for approximate reasoning about complex objects. Our notion of a complex object includes… (More)