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Abonyi / Feil

Cluster Analysis for Data Mining and System Identification

2007. Buch. xviii, 306 S.: 11 s/w-Tabelle, Bibliographien. Hardcover
Birkhäuser ISBN 978-3-7643-7987-2
Format (B x L): 21 x 29,7 cm
Gewicht: 1400 g
In englischer Sprache
The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.

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Professional/practitioner

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Webcode: beck-shop.de/hoey
Detailed overview of the most powerful algortihms and approaches for data mining and system identification is presented Extensive references give a good overview of the current state of the application of computational intelligence in data mining and system identification, and suggest further reading for additional research Numerous illustrations to facilitate the understanding of ideas and methods presented Supporting MATLAB files, available at the website www.fmt.uni-pannon.hu/softcomp create a computational platform for exploration and illustration of many concepts and algorithms presented in the book