Boosting into a New Terminological Era

M. Schmid; O. Gefeller; T. Hothorn

doi:10.1055/s-0038-1627042

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2012; 51(02): 150-151
DOI: 10.1055/s-0038-1627042

Focus Theme – Editorial

Schattauer GmbH

Boosting into a New Terminological Era

M. Schmid

¹Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

,

O. Gefeller

¹Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

,

T. Hothorn

²Institut für Statistik, Ludwig-Maximilians-Universität, München, Germany

› Author Affiliations

Abstract

Full Text

References

References
1 Clayton PD, Narus SP, Huff SM, Pryor TA, Haug PJ, Larkin T. et al Building a comprehensive clinical information system from components - The approach at intermountain health care. Methods Inf Med 2003; 42 (01) 1-7.
2 Lechleitner G, Pfeiffer KP, Wilhelmy I, Ball M. Cerner Millennium (TM): The Innsbruck experience. Methods Inf Med 2003; 42 (01) 8-15.
3 Gell G, Schmucker P, Pedevilla M, Leitner H, Naumann J, Fuchs H. et al SAP and partners: IS-H (TM) and IS-H*MED (TM). Methods Inf Med 2003; 42 (01) 16-24.
4 Haux R, Seggewies C, Baldauf-Sobez W, Kullmann P, Reichert H, Luedecke L. et al Soarian (TM) - Workflow management applied for health care. Methods Inf Med 2003; 42 (01) 25-36.
5 Kuhn KA, Lenz R, Elstner T, Siegele H, Moll R. Experiences with a generator tool for building clinical application modules. Methods Inf Med 2003; 42 (01) 37-44.
6 Giuse DA. Provider order entry with integrated decision support: from academia to industry. Methods Inf Med 2003; 42 (01) 45-50.
7 Schattauer-Gmb H. Instructions to Guest Editors. Stuttgart (updated 2012 Jan 2). Available from http://www.schattauer.de/fileadmin/assets/zeitschriften/methods/guest_editors.pdf.
8 Bühlmann P, Hothorn T. Boosting algorithms: Regularization, prediction and model fitting. Stat Sci 2007; 22 (04) 477-505.
9 Freund Y, Schapire RE. A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 1997; 55 (01) 119-139.
10 Friedman J, Hastie T, Tibshirani R. Additive logistic regression: A statistical view of boosting. Ann Stat 2000; 28 (02) 337-374.
11 Bühlmann P, Yu B. Boosting with the L-2 loss: Regression and classification. J Am Stat Assoc 2003; 98 (462) 324-339.
12 Hastie T, Tishirani R. Generalized additive models. Stat Sci 1986; 1 (03) 297-318.
13 Fan JQ, Lv JC. A Selective Overview of Variable Selection in High Dimensional Feature Space. Stat Sinica 2010; 20 (01) 101-148.
14 Hofner B, Hothorn T, Kneib T, Schmid M. A Framework for Unbiased Model Selection Based on Boosting. J Comput Graph Stat 2011; 20 (04) 956-971.
15 Ziegler A. On Novel Approaches for Classification A Proposal for an Interdisciplinary Debate. Methods Inf Med 2010; 49 (03) 205-206.
16 Stollhoff R, Sauerbrei W, Schumacher M. An Experimental Evaluation of Boosting Methods for Classification. Methods Inf Med 2010; 49 (03) 219-229.
17 Bellazzi R, Diomidous M, Sarkar IN, Takabayashi K, Ziegler A, McCray AT. Data Analysis and Data Mining: Current Issues in Biomedical Informatics. Methods Inf Med 2011; 50 (06) 536-544.
18 Adler W, Peters A, Lausen B. Comparison of classifiers applied to confocal scanning laser ophthalmoscopy data. Methods Inf Med 2008; 47 (01) 38-46. Epub 2008/01/24.
19 Chuang LY, Yang CS, Wu KC, Yang CH. Correlation-based gene selection and classification using Taguchi-BPSO. Methods Inf Med 2010; 49 (03) 254-268. Epub 2010/02/06.
20 Ma S, Huang J, Xie Y, Yi N. Identification of Breast Cancer Prognosis Markers using Integrative Sparse Boosting. Methods Inf Med 2012; 51 (02) 160-169.
21 Wang Z. Multi-class HingeBoost: Method and Application to the Classification of Cancer Types Using Gene Expression Data. Methods Inf Med 2012; 51 (02) 170-175.
22 Wang Z. HingeBoost: ROC-Based Boost for Classification and Variable Selection. Int J Biostat 2011 7. 01
23 Bühlmann P, Hothorn T. Twin Boosting: improved feature selection and prediction. Stat Comput 2010; 20 (02) 119-138.
24 Groll A, Tutz G. Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting. Methods Inf Med 2012; 51 (02) 176-185.
25 Kaslow RA, Ostrow DG, Detels R, Phair JP, Polk BF, Rinaldo Jr CR. The Multicenter AIDS Cohort Study: rationale, organization, and selected characteristics of the participants. American Journal of Epidemiology 1987; 126 (02) 310-318. Epub 1987/08/01.
26 Mayr A, Hofner B, Schmid M. The importance of knowing when to stop - a sequential stopping rule for component-wise gradient boosting. Methods Inf Med 2012; 51 (02) 186-194.