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 ...

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...

This is an expository paper, pointing out explicitly the pseudoness of the "F-statistic" used in stepwise procedures for determining the independent variables to be used in a linear prediction ...