79 search results - page 3 / 16 » Bayesian Maximum Margin Principal Component Analysis |
CORR
2007
Springer
13 years 5 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...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
IJAR
2008
13 years 5 months ago
2008
We present Bayesian updating of an imprecise probability measure, represented by a class of precise multidimensional probability measures. Choice and analysis of our class are mot...
ISQED
2000
IEEE
13 years 10 months ago
2000
IEEE
A new algorithm to determine the number and value of realistic worst-case models for the performance of module library components is presented in this paper. The proposed algorith...
BMCBI
2010
13 years 5 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...