中文摘要：

支持向量机是在统计学习理论的基础上发展起来的新一代学习算法,由于其出色的泛化能力,在文本分类、手写识别、数据挖掘、生物信息学等领域中获得了较好的应用.提出了一种光滑支持向量回归算法,实验结果表明,它相对于其它回归训练方法有较快的收敛速度和较高的拟合精度.

英文摘要：

Support vector machines are new learning algorithms based on statistical learning theory. Support vector machines are widely applied to text classification, handwriting recognition, data mining and biological information because of their good generalization ability. In this paper, a smooth support vector regression algorithm is proposed. The experimental results demonstrate that the smooth support vector regression algorithm has quick convergence rate and high fitting precision.