I've been using an interpretable machine learning package for binary decision trees known as IAI.
Long story short: the core method here is known as an 'optimal classifier' (it does not use greedy heuristics such as random forest or XGBoost. But instead evaluates all trees in combination to obtain global optimisation).
So, given the opposing merits of these three models, I would like to compare AUCs on one graph. Suppose then that I had three stored plots:
x <- iai::roc_curve(grid, test_X, test_y, positive_label = 1)
y <- iai::roc_curve(grid, test_X, test_y, positive_label = 1)
z <- iai::roc_curve(grid, test_X, test_y, positive_label = 1)
Is it possible to combine these in one plot? I've tried pROC and "add true" arguments. But I havent had any luck.
I've attached the source of my code, in case that is helpful. Would truly appreciate some help.
Optimal Classifier AUC:
Greedy Methods AUC