Obtaining Confidence Intervals for AUC Plots

Hi all,

I've recently been using a package known as 'iai' for interpretable machine learning.

However, after going through their user guides to obtain a plotted AUC curve, I wondered if it was possible to construct a bootstrapped confidence interval around the AUC.

I've since tried the standard commands in the pROC package, such as 'ci(roc)' and ci.auc(roc). But unfortunately, I've had no success.

I wondered therefore if I had my AUC score (single value), where the object 'grid' is my decision tree learner.

iai::score(grid, train_X, train_y, criterion = "auc")

Further, the AUC is plotted using the following argument:

iai::roc_curve(grid, test_X, test_y, positive_label = 1)

I wondered if anyone can think with these limited arguments on how to construct confidence intervals for the AUC?

Would be appreciated.


This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.