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FUZZIEEE
2007
IEEE
14 years 3 days 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
TFS
2008
117views more  TFS 2008»
13 years 5 months ago
A New Fuzzy Set Merging Technique Using Inclusion-Based Fuzzy Clustering
Abstract--This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzz...
Samia Nefti, Mourad Oussalah, Uzay Kaymak
KES
2005
Springer
13 years 11 months ago
Bayesian Validation of Fuzzy Clustering for Analysis of Yeast Cell Cycle Data
Clustering for the analysis of the gene expression profiles has been used for identifying the functions of the genes and of unknown genes. Since the genes usually belong to multipl...
Kyung-Joong Kim, Si-Ho Yoo, Sung-Bae Cho
FUZZIEEE
2007
IEEE
14 years 3 days ago
Adaptive Optimization of the Number of Clusters in Fuzzy Clustering
In this paper, we present a local, adaptive optimization scheme for adjusting the number of clusters in fuzzy C-means clustering. This method is especially motivated by online app...
Jürgen Beringer, Eyke Hüllermeier
CORR
2011
Springer
154views Education» more  CORR 2011»
12 years 9 months ago
A Fuzzy View on k-Means Based Signal Quantization with Application in Iris Segmentation
— This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters ...
Nicolaie Popescu-Bodorin