Learning Rates of Support Vector Machine Classifiers with Data Dependent Hypothesis Spaces
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| Title | Learning Rates of Support Vector Machine Classifiers with Data Dependent Hypothesis Spaces |
| Authors | |
| Abstract | We study the error performances of -norm Support Vector Machine classifiers based on reproducing kernel Hilbert spaces. We focus on two category problem and choose the data-dependent polynomial kernels as the Mercer kernel to improve the approximation error. We also provide the standard estimation of the sample error, and derive the explicit learning rate. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2012-01-01 |
| Source | Journal of Computers Vol 7, No 1 (2012): Special Issue: Parallel Algorithms, Scheduling and Architectures |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |