Introduction

In the previous chapters, we began our supervised machine learning journey using regression techniques, predicting the continuous variable output on a given set of input data. We will now turn to the other type of machine learning problem: classification. Recall that classification tasks aim to classify given input data into two or more specified number of classes.

So, while regression is a task of estimating a continuous value for given input data (for example, estimating the price of a house given its location and dimensions as input data), classification is about predicting a (discrete) label for given input data. For example, a well-known machine learning classification task is the spam detection of emails, where the task is to predict whether a given email is spam or not_spam. Here, spam and not_spam are the labels for this task and the input data is the email, or rather the textual data contained in the different fields of the email, such as subject, body, and...