Abstract
In this paper, we propose a novel improved algorithm for the rectangular decomposition technique for the purpose of performing fuzzy knowledge discovery from large scaled database in a dynamic environment. To demonstrate its effectiveness, we compare the proposed one which is based on the newly derived mathematical properties with those of other methods with respect to the classification rate, the number of rules, and complexity analysis.
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© 2005 Springer-Verlag Berlin Heidelberg
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Song, J., Im, Y., Park, D. (2005). An Improved Rectangular Decomposition Algorithm for Imprecise and Uncertain Knowledge Discovery. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_45
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DOI: https://doi.org/10.1007/11539506_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28312-6
Online ISBN: 978-3-540-31830-9
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