Don’t dismiss logistic regression: the case for sensible extraction of interactions in the era of machine learning

Don’t dismiss logistic regression: the case for sensible extraction of interactions in the era of machine learning

Abstract Background Machine learning approaches have become increasingly popular modeling techniques, relying on data-driven heuristics to arrive at its solutions. Recent comparisons between these algorithms and traditional statistical modeling techniques have largely ignored the superiority gained...

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Bibliographic Details
Main Authors: Joshua J. Levy, A. James O’Malley
Format: Article
Language:English
Published: BMC 2020-06-01
Series:BMC Medical Research Methodology
Subjects:
Interactions
Random Forest
Logistic regression
Model Explanations
Machine learning
Online Access:http://link.springer.com/article/10.1186/s12874-020-01046-3

Internet

http://link.springer.com/article/10.1186/s12874-020-01046-3

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