Understanding Classification Algorithms

Recall the two types of supervised machine learning: regression and classification. In regression, we predict a numerical target variable. For example, recall the linear and polynomial models from Chapter 2, Data Exploration with Jupyter. Here, we will focus on the other type of supervised machine learning—classification— the goal of which is to predict the class of a record using the available metrics. In the simplest case, there are only two possible classes, which means we are doing binary classification. This is the case for the example problem in this chapter, where we will try to predict whether an employee is going to leave. If we have more than two class labels, then we are doing multi-class classification.

Although there is little difference between binary and multi-class classification when it comes to training models with scikit-learn, the algorithms can be notably different. In particular, multi-class classification...