Anopheles number prediction on environmental and climate variables using Lasso and stratified two levels cross validation

Abstract

This paper deals with prediction of anopheles number using environmental and climate variables. The variables selection is performed by an automatic machine learning method based on Lasso and stratified two levels cross validation. Selected variables are debiased while the predictionis generated by simple GLM (Generalized linear model). Finally, the results reveal to be qualitatively better, at selection, the prediction,and the CPU time point of view than those obtained by B-GLM method.