Before making the predictions, you need to be certain that the model is reliable. To that end, you need to first perform a residual analysis of the error terms and then move on to making the predictions on the test set; and finally, evaluate the model based on the predictions. Let’s see how Kshitij performs residual analysis for multiple linear regression.
Now that the model building is done, let’s go ahead and make inferences on the model.
Let’s summarize what you have learned in this session.
Coming up
In the next segment, you will build a model using recursive feature elimination (RFE), which is an automated technique.