Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 Fundamenta Informaticae

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: valued tolerance relation

Sortuj według:

Ogranicz wyniki do:

Rough Approximations Based on Valued Tolerance Relations

Qin K., Luo J., Pei Z.

Fundamenta Informaticae

2015

Vol. 142, nr 1-4

183--194

Rough set approach for knowledge discovery in incomplete information systems has been extensively studied. This paper conduct a further study of valued tolerance relation based rough approximations. We make an analysis of the existing rough approximabilities and propose a new approach for lower (upper) approximability, which is a generalization of Pawlak approximation operators for complete information system. The approach has also been generalized to fuzzy cases. Some basic properties of the approximation operators are examined.

Data-driven Valued Tolerance Relation Based on the Extended Rough Set

Wang G., Guan L., Wu W., Hu F.

Fundamenta Informaticae

2014

Vol. 132, nr 3

349--363

The classical rough set theory is based on the conventional indiscernibility relation. It is not very good for analyzing incomplete information. Some successful extended rough set models based on different non-equivalence relations have been proposed. The valued tolerance relation is such an extended model of classical rough set theory. However, the general calculation method of tolerance degree needs to know the prior probability distribution of an information system in advance, and it is also difficult to select a suitable threshold. In this paper, a data-driven valued tolerance relation (DVT) is proposed to solve this problem based on the idea of data-driven data mining. The new calculation method of tolerance degree and the auto-selection method of threshold do not require any prior domain knowledge except the data set. Some properties about the DVT are analyzed. Experiment results show that the DVT can get better and more stable classification results than other extended models of the classical rough set theory.