Algorithms for fuzzy clustering methods in c-means clustering with applications
The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. A main reason why we concentrate on fuzzy c-means is that most methodology and application studies in fuzzy clustering use fuzzy c-means, and hence fuzzy c-means should be co...
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| Main Author: | |
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| Other Authors: | , |
| Format: | Book |
| Language: | English |
| Published: |
Berlin
Springer
c2008.
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| Series: | Studies in fuzziness and soft computing
v. 229 |
| Subjects: | |
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| Summary: | The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. A main reason why we concentrate on fuzzy c-means is that most methodology and application studies in fuzzy clustering use fuzzy c-means, and hence fuzzy c-means should be considered to be a major technique of clustering in general, regardless whether one is interested in fuzzy methods or not. Unlike most studies in fuzzy c-means, what we emphasize in this book is a family of algorithms using entropy or entropy-regularized methods which are less known, but we consider the entropy-based method to be another useful method of fuzzy c-means. Throughout this book one of our intentions is to uncover theoretical and methodological differences between the Dunn and Bezdek traditional method and the entropy-based method. We do note claim that the entropy-based method is better than the traditional method, but we believe that the methods of fuzzy c-means become complete by adding the entropy-based method to the method by Dunn and Bezdek, since we can observe natures of the both methods more deeply by contrasting these two. |
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| Physical Description: | xi, 247 p. ill. 24 cm. |
| Bibliography: | Includes bibliographical references (p. [235]-243) and index |
| ISBN: | 9783540787365 (alk. paper) |
| ISSN: | 1434-9922 |