中国中医药信息杂志Issue(1)：39-42,4.DOI:10.3969/j.issn.1005-5304.2016.01.009
基于数据挖掘的围绝经期综合征中医证候分类算法分析
Classification Algorithm Analysis of TCM Syndrome of Menopausal Syndrome Based on Data Mining
摘要
Abstract
Objective To establish the optimum syndrome classification method by using the technology of modern TCM diagnosis and artificial intelligence analysis method for menopausal syndrome differentiation of TCM. Methods Diagnostic information of menopausal syndrome patients was collected and syndromes were classified according to TCM syndrome differentiation standard. Three kinds of common data mining classification algorithm, Bayesian network, K-nearest neighbors and support vector machine, were used for analysis on information data of the four methods of diagnosis of menopausal syndrome.Results The time, classification accuracy, coverage rate and margin curve of establishing TCM syndrome model by the three kinds of algorithm methods under the circumstances of same training and data. The influence of the number of training samples of 3 kinds of algorithm methods was analyzed, and the model established by the three kinds of algorithms was evaluated.Conclusion Bayesian network algorithm is better than the other two methods in the menopausal syndrome classification effect.关键词
围绝经期综合征/中医证候/数据挖掘/分类算法/训练样本/margin曲线Key words
menopausal syndrome/TCM syndrome/data mining/classification algorithm/training samples/margin curve分类
医药卫生引用本文复制引用
吴宏进,许家佗,张志枫,屠立平,张婷婷,徐莲薇,刘巧莲..基于数据挖掘的围绝经期综合征中医证候分类算法分析[J].中国中医药信息杂志,2016,(1):39-42,4.基金项目
国家科技支撑计划（2012BAI37B06）；国家自然科学基金（30873463、81173200、81373556）；国家自然科学基金青年基金（81102558）；上海市重点学科资助项目（S30302、S30303）；上海中医药大学附属龙华医院院级基金科研项目 （）
