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Ish: Utilities of Artificial Intelligence in Poverty Prediction: A Review
Classification And Regression Trees
Leo Breiman, Jerome H. Friedman, Richard A. Olshen +1
Kitob20173 iqtibosABIA quasi-global precipitation time series for drought monitoring
Chris Funk, Pete Peterson, M. F. Landsfeld +7
Maqola20142 iqtibosABINonlinear Dimensionality Reduction by Locally Linear Embedding
Sam T. Roweis, Lawrence K. Saul
Maqola20002 iqtibosABIMeasuring Multiple Deprivation at the Small-Area Level
Michael Noble, Gemma Wright, George Smith +1
Maqola20062 iqtibosABIAsset‐based measurement of poverty
Andrea Brandolini, Silvia Magri, Timothy M. Smeeding
Maqola20102 iqtibosABICombining satellite imagery and machine learning to predict poverty
Neal Jean, Marshall Burke, Sang Michael Xie +3
Maqola20162 iqtibosABIReturn of the Devil in the Details: Delving Deep into Convolutional Nets
Ken Chatfield, Karen Simonyan, Andrea Vedaldi +1
Preprint20142 iqtibosABICombining night time lights in prediction of poverty incidence at the county level
Jianbin Xu, Jie Song, Baochao Li +2
Maqola20212 iqtibosABISustainability and the Digital transition: a literature review
Albérico Travassos Rosário, Joana Carmo Dias
Sharh maqola20222 iqtibosABI