Learning and classification

When we want to automatically identify to which category a specific value (categorical value) belongs, we need to implement an algorithm that can predict the most likely category for the value, based on the previous data. This is called Classification. 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 keyword here is learning (supervised learning in this case), and also 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 are a large number of applications for a classifier. We can find two kinds of problems in classification. The binary classification is where we have only two categories (spam or not spam) and multiclass classification is where many categories are involved (for example...