计算机工程与应用2018，Vol.54Issue(3)：250-254,5.DOI:10.3778/j.issn.1002-8331.1608-0441
基于ROSE和C5.0算法的打鼾者OSAHS初筛模型
Brief modeling study of OSAHS patients screening from snoring persons based on ROSE and C5.0 algorithm
摘要
Abstract
Aiming at the issue that imbalanced data will exist in the snoring patients with Obstructive Sleep Apnea-Hypopnea Syndrome(OSAHS)prediction and analysis by using the data from medical information system. Therefore, on the basis of the clinical research, a screening model based on Random Over-Sampling Examples(ROSE)and C5.0 decision tree algorithm is established. Firstly, to preprocess the collected anthropometry data, remove outliers and fill in the missing value. Then, to apply the ROSE algorithm to balance the preprocessing data. Next, C5.0 classifier is applied to construct the screening model based on the balanced data. Finally, to evaluate the screening effect through 10-fold cross validation. The results demonstrate that this model can effectively improve the screening efficiency of snoring patients with OSAHS.关键词
不均衡数据/初筛模型/随机过采样(ROSE)/C5.0决策树Key words
imbalanced data/screening model/Random Over Sampling Examples(ROSE)/C5.0 decision tree分类
信息技术与安全科学引用本文复制引用
杜国栋,吕云辉,马磊,相艳,邵党国,雷强,胡蓉..基于ROSE和C5.0算法的打鼾者OSAHS初筛模型[J].计算机工程与应用,2018,54(3):250-254,5.基金项目
国家自然科学基金(No.61163021). （No.61163021）
