4 citations · 7 across the 5 of their papers we have counts for
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stat.ML2016★ 1 cited
Regression Trees and Random forest based feature selection for malaria risk exposure prediction
Bienvenue Kouwayè
This paper deals with prediction of anopheles number, the main vector of malaria risk, using environmental and climate variables. The variables selection is based on an automatic m…
stat.ML2015★ 4 cited
Lasso based feature selection for malaria risk exposure prediction
Bienvenue Kouwayè, Noël Fonton, Fabrice Rossi
In life sciences, the experts generally use empirical knowledge to recode variables, choose interactions and perform selection by classical approach. The aim of this work is to per…
stat.ML2015★ 1 cited
Sélection de variables par le GLM-Lasso pour la prédiction du risque palustre
Bienvenue Kouwayè, Noël Fonton, Fabrice Rossi
In this study, we propose an automatic learning method for variables selection based on Lasso in epidemiology context. One of the aim of this approach is to overcome the pretreatme…