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Assessing dengue fever risk in Costa Rica by using climate variables and
  machine learning techniques

Assessing dengue fever risk in Costa Rica by using climate variables and machine learning techniques

23 March 2022
L. Barboza
S. Chou
P. Vásquez
Y. García
J. G. Calvo
Hugo C. Hidalgo
Fabio Sanchez
ArXivPDFHTML

Papers citing "Assessing dengue fever risk in Costa Rica by using climate variables and machine learning techniques"

2 / 2 papers shown
Title
Climate-driven statistical models as effective predictors of local
  dengue incidence in Costa Rica: A Generalized Additive Model and Random
  Forest approach
Climate-driven statistical models as effective predictors of local dengue incidence in Costa Rica: A Generalized Additive Model and Random Forest approach
P. Vásquez
A. Loría
Fabio Sanchez
L. Barboza
10
16
0
30 Jul 2019
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright
A. Ziegler
259
2,776
0
18 Aug 2015
1