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