Exercise

Baseline

Evaluating a classifier relative to an appropriate baseline is important. This is especially true for imbalanced datasets, such as ad click-through, because high accuracy can easily be achieved through always selecting the majority class. In this exercise, you will simulate a baseline classifier that always predicts the majority class (non-click) and look at its confusion matrix, as well as what its precision and recall are.

X_train, y_train, X_test, y_test are available in your workspace. pandas as pd, numpy as np, and sklearn are also available in your workspace.

Instructions

100 XP

Create y_pred an array of zeros with the same length as X_test using np.asarray().
Print the resulting confusion matrix.
Get the precision and recall scores.