Building an interpretable overweight risk prediction model based on machine learning

Supplemental 1: The distribution of participants. Supplemental 2: Correlation analysis between population characteristic. Supplemental 3: Distribution of missing values in participants. Supplemental 4: The classification report of different models. Supplemental 5: Accuracy of the models. Supplemental 6: The variables importance output by SHAP.补充材料1：研究对象的分布情况；补充材料2：人群特征间的相关性分析；补充材料3：研究对象的缺失值分布情况；补充材料4：不同模型的分类报告；补充材料5：各模型的准确率；补充材料6：SHAP (SHapley Additive exPlanations) 输出的变量重要性