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Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
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(Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!
| Inhalt: |
| 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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Auf Bestellung (Lieferzeit unbekannt)
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