Simple guide on how to generate ROC plot for Keras classifier

ROC is a graphic plot illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. The critical point here is "binary classifier" and "varying threshold". I will show you how to plot ROC for multi-label classifier by the one-vs-all approach as well. AUC is the percentage of this area that is under this ROC curve, ranging between 0 1. ROC is a great way to visualize the performance of a binary classifier, and AUC is one single number to summarize a classifier's performance by assessing the ranking regarding separation of the two classes.