plotAUCvsCombinations: Plotting the average AUC as a function of the number of combinations
Description
This function allows to plot the average AUC as a function of the number k-combinations of the n input
variables. If n is the number of input variables, the number of k-combinations of those variables is equal to
$n!/k!(n!-k!)$. Each of these combinations contains the indexes of the input variables selected. For each
combination we can extract a dataset, build a random forest model and perform a cross-validation. We can describe
the performance of each cross-validated model with an 'average' ROC curve and its AUC. The collected auc values
for each combination (dataset) are used by the function to build a diagram of the AUC as a function
of the number of combinations