Description Usage Arguments Author(s)
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
1 | plotAUCvsCombinations(auc_values, num_of_variables, num_of_combinations)
|
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 |
Piergiorgio Palla
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.