计算机应用与软件2016，Vol.33Issue(8)：67-70,4.DOI:10.3969/j.issn.1000-386x.2016.08.015
一种基于 PCA-SVM 的医疗卫生数据挖掘分类方法
A MINING AND CLASSIFICATION METHOD FOR MEDICAL DATA BASED ON PCA-SVM
摘要
Abstract
Current medical data presents the characteristics of large amount,various categories and complicated features,which bring certain challenge to data mining.According to these characteristics of medical data,we propose a data mining and classification method which is based on principal component analysis (PCA)and support vector machine (SVM),and elaborately study the algorithm model of this method and its specific implementation in medical and health sector.In the MATLAB environment we use two datasets of Cardiotocography dataset and Breast Cancer dataset to carry out simulation experiments.It is indicated by experimental results that the method has good classification effect provides a feasible thought for current medical data mining and classification.关键词
医疗卫生数据/数据挖掘/主成分分析/支持向量机Key words
Medical data/Data mining/Principal component analysis/Support vector machine分类
信息技术与安全科学引用本文复制引用
戴炳荣,王晓丽,李超,陈洁,施天行..一种基于 PCA-SVM 的医疗卫生数据挖掘分类方法[J].计算机应用与软件,2016,33(8):67-70,4.基金项目
浦东新区卫生系统学科带头培养计划（PWRd2014－12）；上海市科技创新行动计划项目（13dz1508500）；院地合作专项（13DZ1512103，13DZ1512101）；上海市软科学研究计划项目（14692103000）。 （）
