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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 ...
ICPR
2008
IEEE
13 years 11 months ago
An extended version of the k-means method for overlapping clustering
This paper deals with overlapping clustering, a trade off between crisp and fuzzy clustering. It has been motivated by recent applications in various domains such as information r...
Guillaume Cleuziou
JCB
2002
160views more  JCB 2002»
13 years 4 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
IVC
2007
94views more  IVC 2007»
13 years 4 months ago
Vector quantization and fuzzy ranks for image reconstruction
The problem of clustering is often addressed with techniques based on a Voronoi partition of the data space. Vector quantization is based on a similar principle, but it is a diffe...
Stefano Rovetta, Francesco Masulli
BMCBI
2010
125views more  BMCBI 2010»
13 years 5 months ago
NeatMap - non-clustering heat map alternatives in R
Background: The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the ...
Satwik Rajaram, Yoshi Oono