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.

<p>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,...

Full description

Saved in:
Bibliographic Details
Main Author: Girmaw Abebe Tadesse (11358420) (author)
Other Authors: Laura Ferguson (95312) (author), Caleb Robinson (8345691) (author), Shiphrah Kuria (12250868) (author), Herbert Wanyonyi (21368420) (author), Samuel Murage (21368423) (author), Samuel Mburu (21368426) (author), Rahul Dodhia (13919428) (author), Juan M. Lavista Ferres (13919431) (author), Bistra Dilkina (8345694) (author)
Published: 2025
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!