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 ...

The problem of interaction selection in high-dimensional data analysis has recently received much attention. This note aims to address and clarify several fundamental issues in interaction selection ...

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

In a recent write-up, [David Delony] explains how he built a Wolfram Mathematica-like engine with Python. Core to the system is SymPy for symbolic math support. [David] said being able to work ...