848 search results - page 25 / 170 » Feature selection in a kernel space |
TIP
2011
13 years 2 months ago
2011
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
ICPR
2004
IEEE
14 years 8 months ago
2004
IEEE
Autoassociator is an important issue in concept learning, and the learned concept of a particular class can be used to distinguish the class from the others. For nonlinear autoass...
ICB
2007
Springer
13 years 11 months ago
2007
Springer
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
NIPS
2008
13 years 9 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
WILF
2007
Springer
14 years 1 months ago
2007
Springer
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...