Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Subspace classifier in the Hilbert space
Pattern Recognition Letters
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
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Local Subspace Classifier (LSC) is a new classification technique, which is closely related to the subspace classification methods, and a heir of prototype classification methods. And it is superior to both of them. In this paper, a method of improving the performance of Local Subspace Classifier is presented. It is to avoid the intersection of the local subspaces representing the respective categories by mapping the original feature space into RKHS (Reproducing Kernel Hilbert Space).