Evaluation of machine learning models based on household food insecurity data in Indonesia
Household food insecurity is a critical issue, and accurate prediction models are essential for identifying at-risk households and guiding policy decisions to address this issue.This study compared the effectiveness and stability of two machine learning models: random forests (RF) and AEG KPK842220M Compact Pyrolytic Self Clean Oven In Stainless St