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IBPRIA
2003
Springer
15 years 7 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
ICPR
2008
IEEE
15 years 8 months ago
A uniformity criterion and algorithm for data clustering
We propose a novel multivariate uniformity criterion for testing uniformity of point density in an arbitrary dimensional point pattern . An unsupervised, nonparametric data cluste...
Sanketh Shetty, Narendra Ahuja
BMCBI
2006
200views more  BMCBI 2006»
15 years 1 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
BMCBI
2005
107views more  BMCBI 2005»
15 years 1 months ago
Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach
Background: In testing for differential gene expression involving multiple serial analysis of gene expression (SAGE) libraries, it is critical to account for both between and with...
Jun Lu, John K. Tomfohr, Thomas B. Kepler
ICDCS
2007
IEEE
15 years 8 months ago
Resilient Cluster Formation for Sensor Networks
Sensor nodes are often organized into clusters to facilitate many network operations such as data aggregation. Clustering has to be protected in hostile environments. Otherwise, a...
Donggang Liu