Right now, the examples in the docs are generated from test data that shows very bad/very poorly performing (basically random!) model performance. Update test data to approximate values from a "decently" performing model, so that metrics plots are meaningful/interpretable and demonstrate accurate implementation (i.e., give someone looking at the ROC curve demo a reason to trust that it is a correctly implemented ROC curve!).
Follow-up: can use the results to generate #17.
Right now, the examples in the docs are generated from test data that shows very bad/very poorly performing (basically random!) model performance. Update test data to approximate values from a "decently" performing model, so that metrics plots are meaningful/interpretable and demonstrate accurate implementation (i.e., give someone looking at the ROC curve demo a reason to trust that it is a correctly implemented ROC curve!).
Follow-up: can use the results to generate #17.