Once the model has been built and evaluated, the next step is to validate the model. In the case of logistic regression models or classification models in general, we basically validate the model by comparing the actual class with the predicted class. There are various ways to do this, but the most famous and widely used is the Receiver Operating Characteristic (ROC) curve.
The ROC curve
An ROC curve is a graphical tool to understand the performance of a classification model. For a logistic regression model, a prediction can either be positive or negative. Also, this prediction can either be correct or incorrect.
There are four categories in which the predictions of a logistic regression model can fall: