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ICPR
2008
IEEE
14 years 2 months ago
Incremental clustering via nonnegative matrix factorization
Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF`s batch nature necessitates recomputation of whole basis set for new samples...
Serhat Selcuk Bucak, Bilge Günsel
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
13 years 11 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
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
14 years 7 days ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...
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
WCRE
2010
IEEE
13 years 6 months ago
Evaluating the Impact of Software Evolution on Software Clustering
—The evolution of a software project is a rich data source for analyzing and improving the software development process. Recently, several research groups have tried to cluster s...
Fabian Beck, Stephan Diehl