OpenCV 4 with Python Blueprints - Second Edition

The testing procedure

In order for a trained classifier to be of any practical value, we need to know how it performs when applied to a data sample (also called generalization) that has never been seen before. To stick to our example shown earlier, we want to know which class the classifier predicts when we present it with a previously unseen picture of a cat or a dog.

More generally speaking, we want to know which class the ? sign, in the following screenshot, corresponds to, based on the decision boundary we learned during the training phase:

From the preceding screenshot, you can see why this is a tricky problem. If the location of the ...