Regression Analysis and How to Use It

Welcome to regression analysis! This chapter covers a different type of supervised learning, where the variable of interest is not categorical but quantitative. We will focus on different modes of linear regression. We will start by learning what linear models do and how they are estimated, using one of the oldest and simplest procedures—ordinary least squares (OLS). Next, we will evaluate how well a model fits data using statsmodels. Then, we will move on to the Bayesian linear regression model and ridge regression; this is a means of regularized linear regression. This is followed by least absolute shrinkage and selection operator (LASSO) regression, which is another regularized regression approach. Finally, we will discuss spline interpolation. While this is technically not considered to be a type of regression, it's still a...