关键词: 决策树, KL距离, 非平衡数据集, 慢性阻塞性肺病, 中医

Abstract: Chronic Obstructive Pulmonary Disease（COPD） is a progressive disease that makes patients hard to breathe and affects their quality of life. Spirometry is the main way to confirm the diagnosis of COPD.In order to reduce some unnecessary examinations and rebuild the harmonious relationship between doctors and patients. This work adopts the K-L divergence based decision tree to build classification model on the collected clinical dataset and uses this model to screen the patients from the point of view of traditional chinese medical. This experiment compars with three other classic decision trees including ID3, C4.5 and CART across F-Measure, G-Mean, AUROC and AUPRC respectively. The experimental results show that the proposed decision tree obtains the best result among the other classic decision trees and the corresponding values of F-Measure, G-Mean, AUROC and AUPRC are 0.92, 0.894, 0.907 and 0.9. Finally, the proposed decision tree is applied to clinic of TCM. The AUROC of the proposed method reaches 0.823, which achieves expected effect.

Key words: decision tree, K-L divergence;imbalanced datasets, Chronic Obstructive Pulmonary Disease（COPD）, Traditional Chinese medicine