IITA-UUwp2/Mapping-aflatoxin-risk-in-maize-using-machine-learning

These are files associated with the prediction of aflatoxin risk levels in maize using various ensemble and non-ensemble machine learning methods in east and southern Africa countries ## README This work is licensed under CC BY 4.0 Files for predicting aflatoxin risk in maize. "cleaned_afla_FINALmonthly24_nonzero.csv" is the aflatoxin risk database with the various satellite based predictors "Classified_Risk_MutipleModels_Aflatoxin_2024_Final.R" is the workflow used to model aflatoxin risk in Maize "prediction_afla_dry2021.tif" & "prediction_afla_dry2018.tif" are the output predictions in current conditions "prediction_afla_dry2021F.tif" & "prediction_afla_dry2018F.tif" are the output predictions in future conditions (assumptions that rainfall will decrease by 1% and temperature will increase with 1%)