Machine Learning for Classification
Once our data has been prepared with some cleaning, feature selection, and feature engineering, we can begin using machine learning algorithms. As we saw in the previous chapter, machine learning falls into three broad categories: supervised, unsupervised, and reinforcement learning. Classification falls under supervised learning, since we have targets or labels in our data. For example, we will look at a credit card loan default dataset here first. This dataset has labels for each data point, indicating whether someone defaulted on a credit card payment.
We will learn the basics of classification with machine learning in this chapter using the sklearn and statsmodels packages. In this chapter, we'll cover the following topics:
- Machine learning classification algorithms for binary and multi-class classification
- Using machine learning classification algorithms for feature selection
Let's begin by covering some...
