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Fuzzy cluster analysis. Methods for classification, data analysis and image recognition. (English) Zbl 0944.65009

Chichester: Wiley. x, 289 p. (1999).
In the preface the authors write as follows: “When writing this book, our intention was to give a self-contained and methodological introduction to fuzzy cluster analysis with its areas of application and to provide a systematic description of different fuzzy clustering techniques, from which the user can choose the methods appropriate for his problem.” I think the book very well attains these goals. The algorithms presented are theoretically justified and there are plenty of examples, which show how the methods work in real life problems. In addition the authors have made the software and data sets, used in the examples, available on Internet.
In the first chapter the authors give a theoretical framework for the practical algorithms. The rest of the book is devoted to different kinds of fuzzy clustering techniques. The topics discussed include clustering the data, recognizing linear structures in the data, detecting boundaries and edges in images and detecting rectangles and polygons.
Reviewer: O.Kaleva (Tampere)

MSC:

65C60 Computational problems in statistics (MSC2010)
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62-07 Data analysis (statistics) (MSC2010)

Software:

Genocop; fc
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