Using novel support vector machines for efficient classification

Yong Wang; Wei Zhang; Jun Chen; Li Xiao; Jianfu Li

doi:10.1117/12.784051

9 January 2008 Using novel support vector machines for efficient classification

Yong Wang, Wei Zhang, Jun Chen, Li Xiao, Jianfu Li

Proceedings Volume 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials; 67944F (2008) https://doi.org/10.1117/12.784051
Event: ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 2007, Gifu, Japan

Abstract

An Improved Support Vector Machines was proposed which starts with a small set and then sequentially expands to include feature space informative data points into the set. These feature space informative data points will be identified by solving a small least squares problem. The approach provides a mechanism to determine the set size automatically and dynamically and the set generated by this method will be more representative than the one by purely random selection. All advantages of SVM for dealing with nonlinear classification problem are retained.

Citation Download Citation

Yong Wang, Wei Zhang, Jun Chen, Li Xiao, and Jianfu Li "Using novel support vector machines for efficient classification", Proc. SPIE 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 67944F (9 January 2008); https://doi.org/10.1117/12.784051

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