摘要
介绍和比较了支持向量机分类器和最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最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 U CI bench-m ark数据集。实验结果表明 。
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.
出处
《控制与决策》
EI
CSCD
北大核心
2003年第3期358-360,共3页
Control and Decision
基金
国家 973重点基础研究发展基金资助项目 ( G19980 3 0 415 )
关键词
支持向量机
分类器
诊断
Support vector machine
Classifiers
Diagnoses
