The ML models, Logistic Regression (LR) and Gradient Boosting (GB) models, outperformed Window Average (WA) model across the IPC AMN categories. All models achieved an AUC >0.9 for forecasting extreme malnutrition risk (). The WA model struggled in the lower ranges of the IPC AMN scale, particularly in the [10%, 15%) range, whereas the GB model performed consistently well across the ranges.
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https://figshare.com/articles/dataset/The_ML_models_Logistic_Regression_LR_and_Gradient_Boosting_GB_models_outperformed_Window_Average_WA_model_across_the_IPC_AMN_categories_All_models_achieved_an_AUC_0_9_for_forecasting_extreme_malnutrition_risk_The_WA_model_struggled_in_the_l/29076809
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The ML models, Logistic Regression (LR) and Gradient Boosting (GB) models, outperformed Window Average (WA) model across the IPC AMN categories. All models achieved an AUC >0.9 for forecasting extreme malnutrition risk (). The WA model struggled in the lower ranges of the IPC AMN scale, particularly in the [10%, 15%) range, whereas the GB model performed consistently well across the ranges.
创建时间：
2025-05-14
