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» K-means clustering via principal component analysis
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APWEB
2006
Springer
13 years 11 months ago
Generalized Projected Clustering in High-Dimensional Data Streams
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
Ting Wang
BMCBI
2010
125views more  BMCBI 2010»
13 years 7 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
CIBCB
2006
IEEE
13 years 9 months ago
A New Hybrid Approach for Unsupervised Gene Selection
In recent years, unsupervised gene (feature) selection has become an integral part of microarray analysis because of the large number of genes and complexity in biological systems....
Young Bun Kim, Jean Gao
CCGRID
2008
IEEE
14 years 2 months ago
Using Dynamic Condor-Based Services for Classifying Schizophrenia in Diffusion Tensor Images
— Diffusion Tensor Imaging (DTI) provides insight into the white matter of the human brain, which is affected by Schizophrenia. By comparing a patient group to a control group, t...
Simon Caton, Matthan Caan, Sílvia Delgado O...
ICPR
2008
IEEE
14 years 2 months ago
Quantitative analysis of Iaido proficiency by using motion data
The purpose of this research is to make a quantitative analysis of Iaido (the Japanese art of using the Japanese sword) proficiency with multivariate data analysis. We carried out...
Woong Choi, Sho Mukaida, Hiroyuki Sekiguchi, Kozab...