基于三种分类算法的CTG数据应用研究  

Research on CTG Data Application Based on Three Classification Algorithms

作　　者：刘青松 瞿颖秋 张晓良 

机构地区：[1]重庆理工大学理学院,重庆

出　　处：《应用数学进展》2021年第1期305-310,共6页Advances in Applied Mathematics

摘　　要：本文采用邻近算法、决策树、支持向量机三种分类方法对胎心宫缩监数据(CTG)进行分类分析,得出每种方法的分类结果,并就每种方法的准确率、误判率进行判别。通过研究表明,决策树可以对实际数据进行很好的分类。In this paper, three classification methods, namely proximity algorithm, decision tree and support vector machine, are used to classify and analyze the fetal heart contractions (CTG) data. The classification results of each method were obtained, and the accuracy and misjudgment rates of each method were identified. The results show that decision tree can classify the actual data well.

关 键 词：邻近算法 决策树 SVM 分类 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]