|
|||||
|
|
Incremental support vector machine algorithm based on multi-kernel learning |
|
| Authors: | Zhi yu Li Jun feng Zhang Shou song Hu |
| Affiliation: | 1. Research Institute of Unmanned Aircraft, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China 2. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China 3. College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China |
| Abstract: | A new incremental support vector machine (SVM) algorithm is proposed which is based on multiple kernel learning.Through introducing multiple kernel learning into the SVM incremental learning,large scale data set learning problem can be solved effectively.Furthermore,different punishments are adopted in allusion to the training subset and the acquired support vectors,which may help to improve the performance of SVM.Simulation results indicate that the proposed algorithm can not only solve the model selection problem in SVM incremental learning,but also improve the classification or prediction precision. |
| Keywords: | support vector machine (SVM) incremental learning multiple kernel learning (MKL) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |