Comprehensive Guide on ROC Curve

The ROC (Receiver Operating Characteristic) curve is a way to visualise the performance of a binary classifier. Here, you can interpret 0 as negative and 1 as positive. In order to classify whether a data item is negative or positive, we need to first decide on the classification threshold. For instance, suppose we have trained a model like logistic regression, and this model predicted a $0.4$ probability that a particular observation is negative, and a $0.6$ probability that the observation is positive. If we set the classification threshold to be $0.5$,