Title :
Separable kernels and its application on model selection
Author :
Wu, Tao ; He, Han-gen
Author_Institution :
Dept. of Autom. Control, Nat. Univ. of Defense Technol., Changsha, China
Abstract :
This paper presents some theorems about separable kernels: when a kernel is separable for the given data and how to make a kernel to be separable. Based on these theorems, a new method of kernels parameters´ selection is presented. The advantage of this new method is its efficiency. The experiments have shown that this method can get satisfactory results quickly.
Keywords :
operating system kernels; optimisation; parameter estimation; support vector machines; model selection; optimization; parameter selection; separable kernel function; support vector machines; Equations; Helium; Kernel; Linear algebra; Pattern recognition; Statistical learning; Sufficient conditions; Support vector machines; Testing; Training data;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259685
