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A comparison of statistical learning methods on the GUSTO database

โœ Scribed by Marguerite Ennis; Geoffrey Hinton; David Naylor; Mike Revow; Robert Tibshirani

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
101 KB
Volume
17
Category
Article
ISSN
0277-6715

No coin nor oath required. For personal study only.

โœฆ Synopsis

We apply a battery of modern, adaptive non-linear learning methods to a large real database of cardiac patient data. We use each method to predict 30 day mortality from a large number of potential risk factors, and we compare their performances. We find that none of the methods could outperform a relatively simple logistic regression model previously developed for this problem.

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