Cluster Analysis for Data Mining and System Identification / Edition 1

by Jïnos Abonyi, Balïzs Feil

Overview

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.

Product Details

ISBN-13:	9783764379872
Publisher:	Birkh�user Basel
Publication date:	08/17/2007
Edition description:	2007
Pages:	306
Product dimensions:	8.27(w) x 11.69(h) x 0.03(d)

Table of Contents

Classical Fuzzy Cluster Analysis.- Visualization of the Clustering Results.- Clustering for Fuzzy Model Identification — Regression.- Fuzzy Clustering for System Identification.- Fuzzy Model based Classifiers.- Segmentation of Multivariate Time-series.