A Relative Tolerance Relation of Rough Set in Incomplete Information

Rough Set Approach to Incomplete Information Systems

In the paper we present Rough Set approach to reasoning in incomplete information systems. We propose reduction of knowledge that eliminates only that information, which is not essential from the point of view of classification or decision making. In our approach we make only one assumption about unknown values: the real value of a missing attribute is one from the attribute domain. However, we...

A Modified Rough Set Approach to Incomplete Information Systems

The key point of the tolerance relation or similarity relation presented in the literature is to assign a “null” value to all missing attribute values. In other words, a “null” value may be equal to any value in the domain of the attribute values. This may cause a serious effect in data analysis and decision analysis because the missing values are just “missed” but they do exist and have an inf...

Rough Fuzzy Set in Incomplete Fuzzy Information System Based on Similarity Dominance Relation

The purpose of this paper is to introduce the concept of dominance-based rough set into the incomplete fuzzy decision system. In such information system, all unknown values are considered as lost, the similarity dominance relation is then used to construct information granules. The lower and upper rough fuzzy approximations in terms of the similarity dominance relation are presented, from which...

Extension of Rough Set under Incomplete Information Systems

Rough Set Extension Model of Incomplete Information System

This paper investigated the incomplete information system in which situation of the more missing or absent unknown values. Based on the original characteristic relation, we proposed a new reflective relation which was controlled by the parameter alpha, beta. By analyzing illustrative examples and comparing to the original characteristic relation, this paper indicated the validity and practicabi...