Random Forest Framework Customized to Handle Highly Correlated Variables: An Extensive Experimental Study Applied to Feature Selection in Genetic Data

Christine Sinoquet, Kamel Mekhnacha. Random Forest Framework Customized to Handle Highly Correlated Variables: An Extensive Experimental Study Applied to Feature Selection in Genetic Data. In Francesco Bonchi, Foster J. Provost, Tina Eliassi-Rad, Wei Wang 0010, Ciro Cattuto, Rayid Ghani, editors, 5th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2018, Turin, Italy, October 1-3, 2018. pages 217-226, IEEE, 2018. [doi]

Abstract

Abstract is missing.