Ken Koon Wong digs into ROC and the area under the curve (AUC):
We see ROC-AUC so often with classification models, we know the higher the better, but there is always that, well it depends scenario. I’ve always wanted to know what the pitfall is, how to avoid it, and how to do better. Let’s go from the basics on how to code ROC-AUC from scratch to decision curve analysis!
Click through to learn how to calculate ROC and dig into the topic a bit. H/T R-Bloggers.