Figure 5.

A flowchart of the feature selection methodology: the features, stored in a matrix, are used to train a random forest model, this model provides a feature important estimation; the procedure is cross-validated with a 5-fold for 1, 000 times, at each round taking into account the selected feature. Finally, a statistical test of hypothesis establishes which features have been selected a significant number of times.