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CEC
2009
IEEE
13 years 10 months ago
Automatic clustering with multi-objective Differential Evolution algorithms
—This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performa...
Kaushik Suresh, Debarati Kundu, Sayan Ghosh, Swaga...
IAJIT
2008
115views more  IAJIT 2008»
13 years 5 months ago
Optimal Fuzzy Clustering in Overlapping Clusters
: The fuzzy c-means clustering algorithm has been widely used to obtain the fuzzy k-partitions. This algorithm requires that the user gives the number of clusters k. To find automa...
Ouafae Ammor, Abdelmounim Lachkar, Khadija Slaoui,...
TKDE
2008
197views more  TKDE 2008»
13 years 5 months ago
Agglomerative Fuzzy K-Means Clustering Algorithm with Selection of Number of Clusters
In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
IJIT
2004
13 years 6 months ago
On the Noise Distance in Robust Fuzzy C-Means
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...
FUZZIEEE
2007
IEEE
13 years 12 months ago
Prototype-less Fuzzy Clustering
Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...
Christian Borgelt