We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...