Receiver Operating Characteristic Curve

Recall the True Positive Rate, which we discussed earlier. It is also called sensitivity. Also recall that what we try to do with a logistic regression model is find a threshold value such that above that threshold value, we predict that our input falls into a certain class, and below that threshold, we predict that it doesn't.

The Receiver Operating Characteristic (ROC) curve is a plot that shows how the true positive and false positive rates vary for a model as the threshold is changed.

Let's do an exercise to enhance our understanding of the ROC curve.

Exercise 6.12: Computing and Plotting ROC Curve for a Binary Classification Problem

The goal of this exercise is to plot the ROC curve for a binary classification problem. The data for this problem is used to predict whether or not a mother will require a caesarian section to give birth.

Note

The dataset that you will be using in this chapter can be found...