MULTI-LAYER SUPPORT VECTOR MACHINE AND ITS APPLICATION
Based on Statistical Learning Theory (SLT), Support Vector Machine (SVM), which is a new kind of machine learning method that is used for classification and regression. SVM is considered as two layers learning machine since it maps the original space into a high dimensional feature space, i.e., input layer and high dimensional feature space layer. If the high dimensional feature space layer is considered as a new problems input layer and the new problem is also solved by SVM, the new problem can be solved by SVMs named Multi-Layer SVM (MLSVM). MLSVM is composed of input layer and at least one layer high dimensional feature space layer. In this paper, m-th order ordinary differential equations are solved by MLSVM for regression. Experimental results indicate that MLSVM can effectively solve the problem of ordinary differential equations. Thus, MLSVM exhibits its great potential to solve other complex problems.
Support Vector Machine Multi-Layer SVM m-th order ordinary differential equations kernel function
YOU-XI WU LEI GUO YAN LI XUE-QIN SHEN WEI-LI YAN
School of Computer Science and Software, Hebei University of Technology, Tianjin 300130,China Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability School of Management,Hebei University of Technology,Tianjin 300130,China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
3627-3631
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）