Case-based reasoning is a paradigm inmachine learningwhose idea is that a new problem can be solved by noticing its similarity to a set of problems previously solved. We propose a new approach to case-based reasoning. It is based on rough set theory that is amathematical theory for reasoning about data. More precisely, we adopt Dominance-based Rough Set Approach (DRSA) that is particularly appr...

Dominance-based rough set introduced by Greco et al. is an extension of Pawlak’s classical rough set theory by using dominance relations in place of equivalence relations for approximating sets of preference ordered decision classes satisfying upward and downward union properties. This paper introduces the concept of indexed blocks for representing dominance-based approximation spaces. Indexed ...

The dominance–based rough set approach plays an important role in the development of the rough set theory. It can be used to express the inconsistencies coming from consideration of the preference–ordered domains of the attributes. The purpose of this paper is to further generalize the dominance–based rough set model to fuzzy environment. The constructive approach is used to define the intuitio...

Dominance-based Rough Set Approach (DRSA) has been proposed to deal with multi-criteria classification problems, where data may be inconsistent with respect to the dominance principle. In this paper, we consider different measures of the quality of approximation, which is the value indicating how much inconsistent the decision table is. We begin with the classical definition, based on the relat...

Dominance-based Rough Set Approach (DRSA) has been proposed to deal with multi-criteria classification problems, where data may be inconsistent with respect to the dominance principle. However, in real-life datasets, in the presence of noise, the notions of lower and upper approximations handling inconsistencies were found to be excessively restrictive which led to the proposal of the variable ...

The paper investigates relationships between chemical structure, surface active properties and antibacterial activity of 70 bis-quaternary imidazolium chlorides. Chemical structure and properties of imidazolium chlorides were described by 7 condition attributes and antimicrobial properties were mapped by a decision attribute. Dominance-based Rough Set Approach (DRSA) was applied to discover a p...

Dominance-based Rough Set Approach (DRSA) is an extension of classical Rough Set Theory (RST). Approximation of class unions is a very important approach in DRSA. Aiming at the disadvantage of the classical method we presented a new methodology for approximation of class unions based on dominance-matrix. It only needs to calculate the dominance-matrix and does not need to consider the preferenc...

Attribute reduction (also called feature subset selection) plays an important role in rough set theory. Different from the classical attribute reduction algorithms, the methods of attribute reduction based on covering rough sets appear to be suitable for numerical data. However, it is time-consuming in dealing with the large-scale data. In this paper, we study the problem of attribute reduction...

the aim of this paper is to introduce and study set- valued homomorphism on lattices and t-rough lattice with respect to a sublattice. this paper deals with t-rough set approach on the lattice theory. the result of this study contributes to, t-rough fuzzy set and approximation theory and proved in several papers. keywords: approximation space; lattice; prime ideal; rough ideal; t-rough set; set...