On the local reduction of information system

Authors:
Degang Chen;Eric C. C. Tsang
Affiliations:
Department of Mathematics and Physics, North China Electric Power University, Beijing, P.R. China;Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong
Venue:
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Year:
2005

Citing 5
Cited 0

Rough set approach to incomplete information systems

Information Sciences: an International Journal
Rough set methods in feature selection and recognition

Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Maximal consistent block technique for rule acquisition in incomplete information systems

Information Sciences: an International Journal
Approaches to knowledge reduction based on variable precision rough set model

Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
Knowledge reduction in random information systems via Dempster-Shafer theory of evidence

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper the definition of local reduction is proposed to describe the minimal description of a definable set by attributes of the given information system. The local reduction can present more optimal description for single decision class than the existing relative reductions. It is proven that the core of reduction or relative reduction can be expressed as the union of the cores of local reductions. The discernibility matrix of reduction and relative reduction can be obtained by composing discernibility matrixes of local reduction.