title: What subject matter questions motivate the use of machine learning approaches compared to statistical models for probability prediction?
abstract: This is a discussion of the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler.
authors.affiliation: Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center, Johannes Gutenberg University Mainz, 55101 Mainz, Germany.
authors.forename: Harald
authors.initials: H
authors.lastname: Binder
mesh_terms: D001185:Artificial Intelligence; D001699:Biometry; D006801:Humans; D015233:Models, Statistical; D009042:Motivation; D011336:Probability
keywords: Added value; External knowledge; Logistic regression; Risk prediction; Uncertainty