基于特征可分性的核函数自适应构造  

Adaptive Construction for Kernel Function Based on the Feature Discriminability

作　　者：任双桥[1] 魏玺章[1] 黎湘[1] 庄钊文[1] 

机构地区：[1]国防科技大学电子科学与工程学院空间电子信息技术研究所,长沙410073

出　　处：《计算机学报》2008年第5期803-809,共7页Chinese Journal of Computers

基　　金：国家自然科学基金(60402032)资助

摘　　要：核函数的选择与构造是支撑向量机研究中的关键问题和难点.该文针对该问题,首先讨论了特征空间的线性可分性,推导了其判别条件.然后,根据特征完全可分条件,基于函数逼近论和核函数的基本性质,提出了自适应多项式核函数和B-样条核函数模型,给出了模型参数的估计算法.实测数据仿真实验结果表明,与经典的核函数相比,该文提出的算法在分类性能上取得了明显改善.This paper firstly gives the distinguishable condition for separating the features space by linear classification hyper surface. Then the paper puts forward a novel adaptive construction algorithm for the kernel function, which is based on the feature distinguishable condition and the property of kernel function. This new kernel functions model includes the polynomial model and the B-Spline model. As the experimental results shown, validated with the actually measuring data, the performance of the new adaptive kernel function, such as classification capability and generalized capability are improved obviously in contrast to the classical kernel function.

关 键 词：支撑向量机 特征可分性 核函数 多项式 B-样条 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]