10. Explain the ROC curve, and how does it work?
The ROC curve is a graph that shows the True Positive Rate on the y-axis and the False Positive Rate on the x-axis. It is used in binary classification.The ratio between False Positives and the total number of negative samples is used to compute the False Positive Rate (FPR), whereas the ratio between True Positives and the total number of positive samples is used to get the True Positive Rate (TPR).
