【摘要】 支持向量机是一种基于统计学习理论的新颖的机器学习方法,该方法已广泛用于解决分类和回归问题。该文利用支持向量回归算法中结构风险函数的性质以及KT条件,提出一种回归中的异常值检测方法。仿真实验结果表明了所给方法的可行性和有效性。更多还原

【Abstract】 Support vector machines(SVM)are a kind of novel machine learning methods,based on statistical learning theory,which have been developed for solving classification and regression problems.A method of outlier detection in re-gression is proposed making use of the character of structure risk function and KT condition in support vector regres-sion in this paper.The results of simulation experiments show the feasibility and effectiveness of the proposed method.更多还原