【摘要】 支持向量机是数据挖掘和机器学习领域中的重要方法之一,最小二乘支持向量机是支持向量机学习算法的重要扩展,在训练速度方面有明显优势。对支持向量机现有的多类分类算法(一对一方法、一对多方法、纠错输出编码方法和最小输出编码方法)引入了最小二乘支持向量机,并应用于睡眠打鼾疾病的诊断预测中,取得了较好的效果。更多还原

【Abstract】 Support Vector Machines(SVM) is one of the most important data mining and machine learning method,and Least Squares Support Vector Machines(LS-SVM) is extended from Support Vector Machines learning algorithm and better in learning speed.The LS-SVM is applied to the multi-class classification methods of SVM including 1-a-r,1-a-1,ECOC and MOC.Then,the multi-class classification methods of LS-SVM are applied to OSAHS diagnoses,which have a good result.更多还原