Year-Independent Prediction of Food Insecurity Using Classical and Neural Network Machine Learning Methods

Year-Independent Prediction of Food Insecurity Using Classical and Neural Network Machine Learning Methods

Current food crisis predictions are developed by the Famine Early Warning System Network, but they fail to classify the majority of food crisis outbreaks with model metrics of recall (0.23), precision (0.42), and f1 (0.30). In this work, using a World Bank dataset, classical and neural network (NN)...

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Bibliographic Details
Main Authors: Cade Christensen, Torrey Wagner, Brent Langhals
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:AI
Subjects:
food crises
humanitarian assistance
logistic regression
neural networks
Online Access:https://www.mdpi.com/2673-2688/2/2/15

Internet

https://www.mdpi.com/2673-2688/2/2/15

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