Foundations of Machine Learning: Part 3 - DZone AI

This post is the seventh one of our series on the history and foundations of econometric and machine learning models. The first four were on econometrics techniques. Part 6 is online here. As we have seen before, modeling here is based on solving an optimization problem, and solving the problem described by equation (6) is all the more complex because the functional space M is large. The idea of boosting, as introduced by Shapire and Freund (2012), is to learn, slowly, from the errors of the model, in an iterative way.