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PR
2006
127views more  PR 2006»
13 years 4 months ago
Unsupervised possibilistic clustering
In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. Since the FCM memberships do not always explain the degrees of belonging for t...
Miin-Shen Yang, Kuo-Lung Wu
WILF
2007
Springer
98views Fuzzy Logic» more  WILF 2007»
13 years 10 months ago
Possibilistic Clustering in Feature Space
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
CMSB
2006
Springer
13 years 8 months ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
ICPR
2008
IEEE
13 years 10 months ago
Unsupervised clustering using hyperclique pattern constraints
A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
13 years 7 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin