Synthetic Data and Generative AI

Chapter 7: Synthetic data, interpretable regression, and submodels

Little known secrets about linear regression

Abstract

The technique discussed here handles a large class of problems. In this article, I focus on a simple one, namely linear regression. I solve it with an iterative algorithm (fixed point) that shares some resemblance to gradient boosting, using machine learning methods and explainable AI, as opposed to traditional statistics. In particular, the algorithm does not use matrix inversion. It is easy to implement in Excel (I provide my spreadsheet) or to automate as a black-box system. Also, it is numerically stable, can generalize to nonlinear problems. Unlike the traditional statistical solution leading to meaningless regression coefficients, ...