支持向量机和最小二乘支持向量机的比较及应用研究

介绍和比较了支持向量机分类器和量小二乘支持向量机分类器的算法。并将支持向量机分类器和量小二乘支持向量机分类器应用于心脏病诊断，取得了较高的准确率。所用数据来自UCI bench—mark数据集。实验结果表明，支持向量机和量小二乘支持向量机在医疗诊断中有很大的应用潜力。

Application of support vector machines and least squares support vector machines to heart disease diagnoses

Nonlinear classifiers algorithms of standard support vector machines (SVM) and least squares support vector machines (LS SVM) are discussed and compared. Then standard SVM nonlinear classifiers and LS SVM nonlinear classifiers are applied to heart disease diagnoses based on UCI benchmark data set. Comparing with other result, high accuracy rate is obtained in the prediction. Application of SVM and LS SVM to disease diagnoses indicates that SVM and LS SVM have potential application in medical.