Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications (Repost)
Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
Publisher: Springer | ISBN: 3540787364 | edition 2008 | PDF | 248 pages | 3,5 mb
Publisher: Springer | ISBN: 3540787364 | edition 2008 | PDF | 248 pages | 3,5 mb
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.