Intelligent data analysis based on rough correlativity matrix

Zhiqiang Geng; Qunxiong Zhu

doi:10.1117/12.521659

2 September 2003 Intelligent data analysis based on rough correlativity matrix

Zhiqiang Geng, Qunxiong Zhu

Proceedings Volume 5253, Fifth International Symposium on Instrumentation and Control Technology; (2003) https://doi.org/10.1117/12.521659
Event: Fifth International Symposium on Instrumentation and Control Technology, 2003, Beijing, China

Abstract

This paper proposes a new data analysis method based on rough sets by rough correlativity matrix. In rough set theory, a table called information system or database is used as a special kind of formal language to represent knowledge, a rough correlativity matrix (RCM) can be seen as an internal representation of equivalence relations. Furthermore, this paper provides a new heuristic attributes reduction algorithm based on matrix computing, such as using matrix correlative implements to replace the relations computing between sets. Finally the paper adopts information transition matrix (ITM) of information theory to represent the certainty or uncertainty decision rules based on probability theory, namely, the information matrix composed of certainty factors gives the degree of belief of decision rules, on the contrary the "invert" ITM composed of coverage factor gives the interpretation of decision rules. The result of instance analysis is shown that it is an efficient and feasible method to deal with decision information table.

Citation Download Citation

Zhiqiang Geng and Qunxiong Zhu "Intelligent data analysis based on rough correlativity matrix", Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); https://doi.org/10.1117/12.521659

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