Learning and classification

When we want to automatically identify which category belongs to a specific value (categorical value), we need to implement an algorithm that can decide the most likely category for the value based on previous data. This is called a classifier. In the words of Tom Mitchell:

"How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes?"

The key word here is learning (supervised learning, in this case) and knowing how to train an algorithm to identify categorical elements. The common examples are spam classification, speech recognition, search engines, computer vision, and language detection, but there is a large number of applications for a classifier. We can find two kinds of problems in classification. The Binary classification is where we only have two categories (Spam or Not Spam) and the Multiclass classification, in which there are many categories involved (such as the...