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.
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References
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© 2003 Springer-Verlag Berlin Heidelberg
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Chin, K.S., Liang, J., Dang, C. (2003). Rough Set Data Analysis Algorithms for Incomplete Information Systems. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_35
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DOI: https://doi.org/10.1007/3-540-39205-X_35
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