In order to discover interesting patterns and dependencies in data, an approach based on rough set theory can be used. In particular, Dominance-based Rough Set Approach (DRSA) has been introduced to deal with the problem of multicriteria classification. However, in real-life problems, in the presence of noise, the notions of rough approximations were found to be excessively restrictive, which l...

Graph theoretical ideas are highly utilized by computer science fields especially data mining. In this field, a data structure can be designed in the form of tree. Covering is a widely used form of data structure in data mining and covering-based rough sets provide a systematic approach to this type of data. In this paper, we study the connectedness of graphs through covering-based rough sets a...

module over a ring is a general mathematical concept for many examples of mathematicalobjects that can be added to each other and multiplied by scalar numbers.in this paper, we consider a module over a ring as a universe and by using the notion of reference points, we provide local approximations for  subsets of the universe.

Attribute reduction has become an important step in pattern recognition and machine learning tasks. Covering rough sets, as a generalization of classical rough sets, have attracted wide attention in both theory and application. This paper provides a novel method for attribute reduction based on covering rough sets. We review the concepts of consistent and inconsistent covering decision systems ...

In this study, we induce some topological structures in the covering rough set models, and construct their closure operators by using the covering upper approximation operators. Furthermore, we show that the minimum set of each of these topological structures is their base, and a partition on the universe of discourse. Finally, we discuss the relationships between some topologies generated by s...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers need...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers nee...

In many data mining applications, cluster analysis is widely used and its results are expected to be interpretable, comprehensible, and usable. Rough set theory is one of the techniques to induce decision rules and manage inconsistent and incomplete information. This paper proposes a method to construct equivalence classes during the clustering process, isolate outlier points and finally deduce...

This article introduces a general framework of multi-granulation fuzzy probabilistic roughsets (MG-FPRSs) models in multi-granulation fuzzy probabilistic approximation space over twouniverses. Four types of MG-FPRSs are established, by the four different conditional probabilitiesof fuzzy event. For different constraints on parameters, we obtain four kinds of each type MG-FPRSs...

Many methods have been proposed to process missing data for information system. In the paper, we modified an algorithm to handle missing value based on covering rough sets model previously reported by Dai Dai and Jianpeng Wang proposed to transform an incomplete information system into a complete information system. The experimental results show that the new version of algorithm is efficient. K...