7. Linear Regression Lab: Data Transformation and Normality Analysis

7. Linear Regression Lab: Data Transformation and Normality Analysis

In this notebook, we'll combine demonstration and hands-on exercises to explore linear regression using scikit-learn. We'll begin by setting up a basic regression framework and then dive into two practical lab exercises. The session will cover how to run simple linear regression, apply transformations to achieve normal distribution of target variables, and implement inverse transformations for regression analysis. Using the Boston housing dataset, we'll examine the MEDV (median value) as our target variable and explore various features for prediction. We'll also discuss methods for assessing data normality, as normally distributed target variables often yield better regression results. This practical session will help you understand both the theoretical concepts and their implementation in Python.

Видео 7. Linear Regression Lab: Data Transformation and Normality Analysis канала My Course