中医诊断模型构建中的两种常用数据挖掘分类技术  

Two Classification Algorithms of Data Mining Frequently Adopted in Creating Diagnosis Model of Traditional Chinese Medicine

作　　者：车立娟[1] 马利庄[2] 

机构地区：[1]上海中医药大学现代教育技术中心,上海201203 [2]上海交通大学电子信息与电气工程学院计算机科学与工程系

出　　处：《数理医药学杂志》2013年第5期550-552,共3页Journal of Mathematical Medicine

基　　金：国家科技重大专项资助项目(2012ZX10005001-004)

摘　　要：决策树和神经网络是经典的数据挖掘分类技术,介绍这两种常用分类技术及其在中医诊断模型构建中的应用,分析总结了算法的优势与不足,以期为研究者在选择算法时提供依据。The creation of diagnosis model of traditional Chinese medicine is the classification of tradi- tional Chinese medicine samples in essence. Classification decision tree and neural network are two classical data mining technologies. These two classification technologies and their application in the creation of diag- nosis model of traditional Chinese medicine are introduced in this paper. The advantages and disadvantages of both technologies are analyzed in detail, providing a basis for researchers to choose the appropriate algo-rithm.

关 键 词：数据挖掘 中医诊断模型 分类算法 

分 类 号：R203[医药卫生—中医学] O236[理学—运筹学与控制论]