In this example, we will combine clustering with classification in a semi-supervised learning problem. We will learn features by clustering unlabeled data, and use the learned features to build a supervised classifier.
Suppose that you own a cat and a dog. Further suppose that you have purchased a smartphone, ostensibly to use to communicate with humans, but in practice just to use to photograph your cat and dog. Your photographs are awesome, and you are certain that your friends and co-workers would love to review all of them in detail. You'd like to be courteous and respect that some people will only want to see your cat photos while others will only want to see your dog photos, but separating the photos is laborious. Let's build a semi-supervised learning system that can classify images of cats and dogs.
Recall from Chapter 3, Classification...
