A comparison of statistical learning methods on the Gusto database

A battery of modern, adaptive non-linear learning methods were applied to a large real database of cardiac patient data. Each method was used to predict 30-day mortality from a large number of potential risk factors, and their perfomances were compared. None of the methods could outperform a relatively simple logistic regression model previously developed for this problem.