title: Variable selection in large margin classifier-based probability estimation with high-dimensional predictors.
abstract: This is a discussion of the 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: Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
authors.forename: Seung Jun
authors.initials: SJ
authors.lastname: Shin
authors.forename: Yichao
authors.initials: Y
authors.lastname: Wu
mesh_terms: D001185:Artificial Intelligence; D011336:Probability; D060388:Support Vector Machine
keywords: Max-type penalty; Regularization; Variable selection