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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書誌詳細

出版年:	PLoS ONE
主要な著者:	Chris Browne, David S Matteson, Linden McBride, Leiqiu Hu, Yanyan Liu, Ying Sun, Jiaming Wen, Christopher B Barrett
フォーマット:	論文
言語:	英語
出版事項:	Public Library of Science (PLoS) 2021-01-01
オンライン･アクセス:	https://doi.org/10.1371/journal.pone.0255519