847 search results - page 6 / 170 » HITS is Principal Components Analysis |
100
Voted
PRL
2006
14 years 10 months ago
2006
A straight line detection algorithm is presented. The algorithm separates row and column edges from edge image using their primitive shapes. The edges are labeled, and the princip...
104
Voted
IJCNN
2006
IEEE
15 years 4 months ago
2006
IEEE
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
101
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BMCBI
2010
14 years 9 months ago
2010
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
ICANN
2007
Springer
15 years 4 months ago
2007
Springer
Treatment of general structured information by neural networks is an emerging research topic. Here we show how representations for graphs preserving all the information can be devi...
85
Voted
CORR
2007
Springer
14 years 10 months ago
2007
Springer
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...