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Fuzzy Rules Generation Method for Pattern Recognition Problems

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Applications of Fuzzy Sets Theory (WILF 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4578))

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Abstract

In the paper we consider the problem of automatic fuzzy rules mining. A new method for generation of fuzzy rules according to the set of precedents is suggested. The proposed algorithm can find all significant rules with respect to wide range of reasonable criterion functions. We present the statistical criterion for knowledge quality estimation that provides high generalization ability. The theoretical results are complemented with the experimental evaluation.

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Francesco Masulli Sushmita Mitra Gabriella Pasi

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© 2007 Springer-Verlag Berlin Heidelberg

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Kropotov, D., Vetrov, D. (2007). Fuzzy Rules Generation Method for Pattern Recognition Problems. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_25

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  • DOI: https://doi.org/10.1007/978-3-540-73400-0_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73399-7

  • Online ISBN: 978-3-540-73400-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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