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CSDA
2008
65views more  CSDA 2008»
15 years 2 months ago
On the number of principal components: A test of dimensionality based on measurements of similarity between matrices
An important problem in principal component analysis (PCA) is the estimation of the correct number of components to retain. PCA is most often used to reduce a set of observed vari...
Stéphane Dray
ENTCS
2006
127views more  ENTCS 2006»
15 years 2 months ago
Component Identification Through Program Slicing
This paper reports on the development of specific slicing techniques for functional programs and their use for the identification of possible coherent components from monolithic c...
Nuno F. Rodrigues, Luís Soares Barbosa
CSDA
2006
81views more  CSDA 2006»
15 years 2 months ago
A recursive approach to detect multivariable conditional variance components and conditional random effects
A complex trait like crop yield is determined by its component traits. Multivariable conditional analysis in a general mixed linear model is helpful in dissecting the gene express...
Jixiang Wu, Dongfeng Wu, Johnie N. Jenkins Jr., Ja...
140
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CIKM
2010
Springer
15 years 1 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
GEOINFO
2004
15 years 3 months ago
Visualization of Geospatial Data by Component Planes and U-matrix
: This paper shows an application of two visualization algorithms of multivariate data, U-matrix and Component Planes, in a matter of exploratory analysis of geospatial data. These...
Marcos Aurélio Santos da Silva, Antôn...