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IJUFKS
2007
108views more  IJUFKS 2007»
13 years 7 months ago
Resampling for Fuzzy Clustering
Abstract. Resampling methods are among the best approaches to determine the number of clusters in prototype-based clustering. The core idea is that with the right choice for the nu...
Christian Borgelt
TKDE
2008
197views more  TKDE 2008»
13 years 7 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...
PR
2006
119views more  PR 2006»
13 years 7 months ago
Fuzzy Bayesian validation for cluster analysis of yeast cell-cycle data
Clustering for the analysis of the genes organizes the patterns into groups by the similarity of the dataset and has been used for identifying the functions of the genes in the cl...
Sung-Bae Cho, Si-Ho Yoo
EPIA
2011
Springer
12 years 7 months ago
Thematic Fuzzy Clusters with an Additive Spectral Approach
This paper introduces an additive fuzzy clustering model for similarity data as oriented towards representation and visualization of activities of research organizations in a hiera...
Susana Nascimento, Rui Felizardo, Boris Mirkin
ICPR
2008
IEEE
14 years 1 months ago
A fuzzy c-means algorithm using a correlation metrics and gene ontology
A fuzzy c-means algorithm was adapted for analyzing microarray data. The adaptation consisted of initialization of fuzzy centroids using gene ontology information and the use of P...
Mingrui Zhang, Terry M. Therneau, Michael A. McKen...