ROC and AUC, Clearly Explained!

ROC (Receiver Operator Characteristic) graphs and AUC (the area under the curve), are useful for consolidating the information from a ton of confusion matrices into a single, easy to interpret graph. This video walks you through how to create and interpret ROC graphs step-by-step. We then show how the AUC can be used to compare classification methods and, lastly, we talk about what to do when your data isn’t as warm and fuzzy as it should be. ⭐ NOTE: When I code, I use Kite, a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I love it! NOTE: This is the revision of a video published earlier. NOTE: This video assumes you already know about Confusion Matrices... https://yo