Rough set data analysis algorithms for incomplete information systems

Authors:
K. S. Chin;Jiye Liang;Chuangyin Dang
Affiliations:
Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong;Department of Computer Science, Shanxi University, Taiyuan, China;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong
Venue:
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Year:
2003

Citing 5
Cited 0

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Abstract

The rough set theory is a relatively new soft computing tool for dealing with vagueness and uncertainty in databases. To apply this theory, it is important to associate it with effective computational methods. In this paper, we focus on the development of algorithms for incomplete information systems and their time and space complexity. In particular, by using measure of significance of attribute which is defined by us, we present a heuristic algorithm for computing the minimal reduct, the time complexity of this algorithm is O(|A|3|U|2), and its space complexity is O(|A||U|). The minimal reduct algorithm is very useful for knowledge discovery in databases.