摘要
支撑矢量机是根据统计学习理论提出的一种新的学习方法 ,即使用核函数在高维空间里进行有效的计算。在模式识别中 ,支撑矢量算法通过训练分类器在某个与输入空间非线性相联的高维空间里进行线性划分 ,从而构造出非线性判别函数。
The support vector machine is a novel type of learning technique, based on statistical learning theory, which uses Mercer kernels for efficiently performing computations in high dimensional spaces. In pattern recognition, the support vector algorithm constructs nonlinear decision functions by training a classifier to perform a linear separation in some high dimensional space which is nonlinearly related to input space.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2001年第9期25-27,52,共4页
Systems Engineering and Electronics
基金
"863"高技术计划基金 ( 86 3-317-0 3-0 5 -99)
国家教育部博士点基金 ( 980 710 9)资助课题
