Exercise

Evaluating a classifier

To evaluate a classifier, we need to test it on images that were not used during training. This is called "cross-validation": a prediction of the class (e.g., t-shirt, dress or shoe) is made from each of the test images, and these predictions are compared with the true labels of these images.

The results of cross-validation are provided as one-hot encoded arrays: test_labels and predictions.

Instructions

100 XP

Multiply the arrays with each other and sum the result to find the total number of correct predictions.
Divide the number of correct answers (the sum) by the length of predictions array to calculate the proportion of correct predictions.