Boosting – An Unusual Yet Attractive Optimiser

T. Hothorn

doi:10.3414/ME13-10-0123

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2014; 53(06): 417-418
DOI: 10.3414/ME13-10-0123

Editorial

Schattauer GmbH

Boosting – An Unusual Yet Attractive Optimiser

Authors

T. Hothorn

¹University of Zurich, Zurich, Switzerland

Abstract

Summary

This editorial is part of a For-Discussion- Section of Methods of Information in Medicine about the papers “The Evolution of Boosting Algorithms – From Machine Learning to Statistical Modelling” [1] and “Ex-tending Statistical Boosting – An Overview of Recent Methodological Developments” [2], written by Andreas Mayr and co authors. It preludes two discussed reviews on developments and applications of boosting in biomedical research. The two review papers, written by Andreas Mayr, Harald Binder, Olaf Gefeller, and Matthias Schmid, give an overview on recently published methods that utilise gradient or likelihood-based boosting for fitting models in the life sciences. The reviews are followed by invited comments [3] by experts in both boosting theory and applications.

Full Text

References

References
1 Mayr A, Binder H, Gefeller O, Schmid M. The Evolution of Boosting Algorithms - From Machine Learning to Statistical Modelling. Methods Inf Med 2014; 53 (06) 419-427.
2 Mayr A, Binder H, Gefeller O, Schmid M. Extending Statistical Boosting - An Overview of Recent Methodological Developments. Methods Inf Med 2014; 53 (06) 428-435.
3 Bühlmann P, Gertheiss J, Hieke S, Kneib T, Ma S, Schumacher M. et al. Discussion of “The Evolution of Boosting Algorithms” and “Extending Statistical Boosting”. Methods Inf Med 2014; 53 (06) 436-445.
4 Bühlmann P, Hothorn T. Boosting algorithms: Regularization, prediction and model fitting. Statistical Science 2007; 22 (04) 477-505. doi: 10.1214/07-STS242 with discussion
5 Scheipl F, Kneib T, Fahrmeir L. Penalized likelihood and Bayesian function selection in regression models. AStA Advances in Statistical Analysis 2013; 97 (04) 349-385. doi: 10.1007/s10182-013-0211-3
6 Johnson BA, Long Q. Survival ensembles by the sum of pairwise differences with application to lung cancer microarray studies. The Annals of Applied Statistics 2011; 5 (02) 1081-1101. doi: 10.1214/10-AOAS426
7 Dubossarsky E, Friedman JH, Ormerod JT, Wand MP. Wavelet-based gradient boosting. Statistics and Computing 2014. doi: 10.1007/s11222-014-9474-0 In press