18th International Conference on Pattern Recognition (ICPR'06) Volume 2 An Approach for Constructing Sparse Kernel Classifier Hong Kong August 20-August 24 ISBN: 0-7695-2521-0
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.235
This paper presents a new approach for constructing sparse kernel classifier with large margin. Firstly, we propose a kernel function pursuit strategy for selecting a small number of kernel functions which are used for expanding final classifier. And then an added constraint controls the sparseness of the final classifier and an approach is provided to solve the optimization problem with L2 loss function and complexity measure. The experiment results show that sparse kernel classifier can achieved higher efficiency for both training and testing without sacrificing prediction accuracy.
Citation:
Zejian Yuan, Yanyun Qu, Yang Yang, Nanning Zheng, "An Approach for Constructing Sparse Kernel Classifier," icpr, vol. 2, pp.560-563, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||