Let's quickly brush up on the topics we learned in Chapter 3, Introduction to Supervised Learning. Supervised learning, as you already know by now, is the branch of machine learning and artificial intelligence that helps machines learn without explicit programming. A more simplified way of describing supervised learning would be developing algorithms that learn from labeled data. The broad categories in supervised learning are classification and regression, differentiated fundamentally by the type of label, that is, continuous or categorical. Algorithms that deal with continuous variables are known as regression algorithms, and those with categorical variables are called classification algorithms.
In classification algorithms, our target, dependent, or criterion variable is a categorical variable. Based on the number of classes, we can further divide them into the following groups:
Binary classification
Multinomial classification
Multi-label classification
In this chapter, we will...