plotAUCvsCombinations: Plotting the average AUC as a function of the number of...

Description Usage Arguments Author(s)

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

Usage

1
plotAUCvsCombinations(auc_values, num_of_variables, num_of_combinations)

Arguments

auc_values

an array with the auc values to plot

num_of_variables

the k dimension of each combination

num_of_combinations

the number of k combinations of the set of the input variables

Author(s)

Piergiorgio Palla


RFmarkerDetector documentation built on May 2, 2019, 3:42 p.m.