Machine learning

Simple and intuitive explanation of ROC curves and AUC

I don’t know why, but it took me a little while to properly make sense of these diagnostics, so I wanted to develop a very simple illustration of the logic behind these concepts. ROC stands for Receiver Operating Characteristics, while AUC is the area under this curve, which is used as a metric for model performance in a classification problem. Perfomance is measured as the ability to maximise true positives, while minimising false positives.