Study on Prediction Model of Phlegm-Dampness Constitution of Traditional Chinese Medicine Based on Random Forest
Objective To establish a model based on Random Forest algorithm that can accurately predict the phlegm-dampness constitution in traditional Chinese medicine and find out the relevant important characteristics.Methods After data preprocessing,a total of 2710 subjects were included,50%of which were phlegm-dampness constitutions;The RFECV method was used to implement feature selection,and the selected feature subset was used to construct the prediction model of phlegm-dampness constitution based on random forest,and the performance of the prediction model was evaluated by six indicators:accuracy,precision,sensitivity,specificity,F1-score and AUC,and compared with SVM and logistic regression models.Results A total of 16 features were used in the prediction model of phlegm-dampness constitution by RFECV feature selection method.In the modeling group and the validation group,the prediction accuracy of the random forest model was 0.907,0.814,the accuracy was 0.936 and 0.827,the sensitivity was 0.885 and 0.806,the specificity was 0.932 and 0.822,the F1-score was 0.910 and 0.816,and the AUC value was 0.970 and 0.901,respectively,which were higher than those of the other two prediction models.Conclusion The prediction model of phlegm-dampness constitution of traditional Chinese medicine based on the random forest model has good performance.This study provides methodological reference for objectified model of TCM constitution type prediction.
Random ForestPhlegm-dampness ConstitutionPredictive ModelsFeature Selection
NETL
NSTL
万方数据
