Multivariate random forest prediction of poverty and malnutrition prevalence.

Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies' programming. However, state of the art models often rely on proprietary data and/or deep or tra...

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Bibliographic Details

Published in:	PLoS ONE
Main Authors:	Chris Browne, David S Matteson, Linden McBride, Leiqiu Hu, Yanyan Liu, Ying Sun, Jiaming Wen, Christopher B Barrett
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2021-01-01
Online Access:	https://doi.org/10.1371/journal.pone.0255519