a b c d e f g h i j k l m n o p q r s t u v w x y z    0 1 2 3 4 5 6 7 8 9 
а б в г д е ж з и й к л м н о п р с т у ф х ц ч ш щ ъ ы ь э ю я 

Скачать Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications (repost) бесплатно

Algorithms for Fuzzy Clustering

Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications (Studies in Fuzziness and Soft Computing)
Springer | April 15, 2008 | ISBN: 3540787364 | 248 pages | PDF | 3.56 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. 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.




:::::::::::::::::::::::::: Visit My Blog for more ::::::::::::::::::::::::::

No mirrors please

PM me if link are dead


Посетители, находящиеся в группе Гости, не могут оставлять комментарии в данной новости.