Multi-class Linear Feature Extraction by Nonlinear PCA

R.P.W. Duin, M. Loog, R. Haeb-Umbach, in: International Conference on Pattern Recognition (ICPR 2000), 2000.

Conference Paper | English
Author
; ;
Abstract
The traditional way to find a linear solution to the feature extraction problem is based on the maximization of the class-between scatter over the class-within scatter (Fisher mapping). For the multi-class problem this is, however, sub-optimal due to class conjunctions, even for the simple situation of normal distributed classes with identical covariance matrices. We propose a novel, equally fast method, based on nonlinear PCA. Although still sub-optimal, it may avoid the class conjunction. The proposed method is experimentally compared with Fisher mapping and with a neural network based approach to nonlinear PCA. It appears to outperform both methods, the first one even in a dramatic way.
Publishing Year
Proceedings Title
International Conference on Pattern Recognition (ICPR 2000)
LibreCat-ID

Cite this

Duin RPW, Loog M, Haeb-Umbach R. Multi-class Linear Feature Extraction by Nonlinear PCA. In: International Conference on Pattern Recognition (ICPR 2000). ; 2000.
Duin, R. P. W., Loog, M., & Haeb-Umbach, R. (2000). Multi-class Linear Feature Extraction by Nonlinear PCA. In International Conference on Pattern Recognition (ICPR 2000).
@inproceedings{Duin_Loog_Haeb-Umbach_2000, title={Multi-class Linear Feature Extraction by Nonlinear PCA}, booktitle={International Conference on Pattern Recognition (ICPR 2000)}, author={Duin, Robert P.W. and Loog, Marco and Haeb-Umbach, Reinhold}, year={2000} }
Duin, Robert P.W., Marco Loog, and Reinhold Haeb-Umbach. “Multi-Class Linear Feature Extraction by Nonlinear PCA.” In International Conference on Pattern Recognition (ICPR 2000), 2000.
R. P. W. Duin, M. Loog, and R. Haeb-Umbach, “Multi-class Linear Feature Extraction by Nonlinear PCA,” in International Conference on Pattern Recognition (ICPR 2000), 2000.
Duin, Robert P. W., et al. “Multi-Class Linear Feature Extraction by Nonlinear PCA.” International Conference on Pattern Recognition (ICPR 2000), 2000.

Link(s) to Main File(s)
Access Level
Restricted Closed Access

Export

Marked Publications

Open Data LibreCat

Search this title in

Google Scholar