The book Three Approaches to Data Analysis [1] presents three approaches to data analysis: (1) Test Theory (TT), founded by Sergei V. Yablonskii; (2) Rough Sets (RS), founded by Zdzislaw I. Pawlak and (3) Logical Analysis of Data (LAD), founded by Peter L. Hammer. These three approaches have much in common. They all are related to Boolean functions and Boolean reasoning. All three data analysis...

In this paper, we propose a new type of matroids, namely covering matroids, and investigate the connections with the second type of covering-based rough sets and some existing special matroids. Firstly, as an extension of partitions, coverings are more natural combinatorial objects and can sometimes be more efficient to deal with problems in the real world. Through extending partitions to cover...

Rough sets, developed by Pawlak [6], are an important tool to describe a situation of incomplete or partially unknown information. One of the algebraic models deals with the pair of the upper and the lower approximation. Although usually the tolerance or the equivalence relation is taken into account when considering a rough set, here we rather concentrate on the model with the pair of two defi...

This paper includes the Rough Sets theory for video deinterlacing that has been both researched and applied. The domain knowledge of several experts influences the decision making aspects of this theory. However, included here are a few studies that discuss the effectiveness of the Rough Sets concept in the field of engineering. Moreover, the studies involving a deinterlacing system that are ba...

Multigranulation rough sets are desirable features in the field of rough set, where this concept is approximated by multiple granular structures. In this study, we employ belief and plausibility functions from evidence theory to characterize the set approximations and attribute reductions in multigranulation rough set theory. First, we show that in an incomplete information system, the pessimis...

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...

Disease forecasting using soft computing techniques is major area of research in data mining in recent years. To classify heart and diabetes diseases, this paper proposes a diagnosis system using cuckoo search optimized rough sets based attribute reduction and fuzzy logic system. The disease prediction is done as per the following steps 1) feature reduction using cuckoo search with rough set th...

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...