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JCB
2002
160views more  JCB 2002»
13 years 7 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, ...
BMCBI
2011
13 years 2 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
PRL
2008
135views more  PRL 2008»
13 years 7 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
CVPR
2010
IEEE
14 years 3 months ago
Clustering Dynamic Textures with the Hierarchical EM Algorithm
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model ...
Antoni Chan, Emanuele Coviello, Gert Lanckriet
ICONIP
2008
13 years 9 months ago
Local Feature Selection in Text Clustering
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...