移动最小二乘支持向量机

基于移动最小二乘逐点逼近思想,移动权被引入到最小二乘支持向量机的误差变量中,得到新算法的模型.此外,证明了用移动最小二乘支持向量机作函数估计与在特征空间中用移动最小二乘法得到的解是一致的,揭示了移动最小二乘支持向量机所选择的核函数相当于移动最小二乘法所选择基函数组.数值试验与实例进一步验证所提出方法的优越性.

Moving least square support vector machine

Based on the idea of the moving least square for point by point approximation, the model of new algorithm was established by introducing the moving weighted function into error variance of least square support vector machine. It was proved that the solution of regression by using moving least square support vector machine coincided with the solution obtained by using moving least square method in the feature space. It also proved that the choice of kernel function of moving least square support vector machine was equivalent to the choice of basis function of moving least square method. The superiority of the proposed method is further shown by the numerical and the practice examples.