Abstract
Methods of Perception-based Data Mining (Data Miners DM) for fuzzy relational data servers are considered in the article. The considering problems of DM are limited by problems of clustering and mining of dependences in the form of fuzzy rules because these problems are especially important in practice. The hybrid algorithm of fuzzy clustering and the way of use of a fuzzy inference system as a DM for fuzzy relational data is offered in the article.
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© 2007 Springer-Verlag Berlin Heidelberg
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Velmisov, A.P., Stetsko, A.A., Yarushkina, N.G. (2007). Data Mining for Fuzzy Relational Data Servers. In: Castillo, O., Melin, P., Ross, O.M., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72434-6_23
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DOI: https://doi.org/10.1007/978-3-540-72434-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72433-9
Online ISBN: 978-3-540-72434-6
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