摘要
心脏病是一类高发病率、高死亡率的疾病,及时且准确地诊断心脏病有利于为患者争取更多的治疗时间,提高患者的康复概率并减少危险。选用UCI提供的心脏病数据集作为实验数据,提出了基于遗传算法(Genetic Algorithm,GA)优化支持向量机(Support Vector Machine,SVM)的心脏病诊断模型GA-SVM。实验结果表明,GA-SVM的分类准确率较高,相较于其他机器学习模型而言具有更强的预测与泛化能力。
Heart disease is a class of diseases with high morbidity and mortality,and timely and accurate diagnosis of heart disease can help to buy more treatment time for patients,improve their recovery probability and reduce risks.The heart disease dataset provided by UCI was selected as the experimental data,and a heart disease diagnosis model(GA-SVM)based on Genetic Algorithm(GA)optimized Support Vector Machine(SVM)was proposed.The experimental results show that GA-SVM has higher classification accuracy and stronger prediction and generalization ability compared with other machine learning models.
作者
吴霆辉
WU Tinghui(School of Mathematical Sciences,South China Normal University,Guangzhou Guangdong 510631,China)
出处
《信息与电脑》
2023年第4期94-97,共4页
Information & Computer
