Model-based boosting 2.0

Journal of Machine Learning Research

Volumn 11, Issue , 2010, Pages 2109-2113

  Hothorn, Torsten ^a   Bühlmann, Peter ^b   Kneib, Thomas ^c   Schmid, Matthias ^d   Hofner, Benjamin ^d  

^a UNIVERSITY OF MUNICH   (Germany)

^b ETH ZURICH   (Switzerland)

^c Institut für Mathematik   (Switzerland)

^d UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

Author keywords

Component wise functional gradient descent; Decision trees; Splines

Indexed keywords

COMPONENTWISE; FUNCTIONAL GRADIENT DESCENT; HIGH DIMENSIONAL DATA; INTERACTION MODEL; LEAST SQUARES ESTIMATE; MODEL-BASED; REGRESSION TREES; RISK FUNCTION;

SPLINES;

DECISION TREES;

EID: 77956921559     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article

References (10)

1. Douglas Bates and Martin Mächler. Matrix: Sparse and Dense Matrix Classes and Methods, 2009. URL http://CRAN. R-project.org/package=Matrix. R package version 0.999375-38.
2. Peter Bühlmann and Torsten Hothorn. Boosting algorithms: Regularization, prediction and model fitting (with discussion). Statistical Science, 22(4):477-505, 2007.
3. 2 loss: Regression and classification. Journal of the American Statistical Association, 98:324-339, 2003.
4. Nora Fenske, Thomas Kneib, and Torsten Hothorn. Identifying risk factors for severe childhood malnutrition by boosting additive quantile regression. Technical report, Institut für Statistik, Ludwig-Maximilians- Universität München, 2009. URL http://epub.ub.uni-muenchen. de/10510/.
5. Jerome H. Friedman, Trevor Hastie, and Robert Tibshirani. Additive logistic regression: a statistical view of boosting (with discussion). The Annals of Statistics, 28:337-407, 2000.
6. Ada L. Garcia, Karen Wagner, Torsten Hothorn, Corinna Koebnick, Hans-Joachim F. Zunft, and Ulrike Trippo. Improved prediction of body fat by measuring skinfold thickness, circumferences, and bone breadths. Obesity Research, 13(3):626-634, 2005.
7. Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, and Benjamin Hofner. mboost: Model-Based Boosting, 2010. URL http://CRAN. R-project.org/package=mboost. R package version 2.0-4.
8. Thomas Kneib, Torsten Hothorn, and Gerhard Tutz. Variable selection and model choice in geoadditive regression models. Biometrics, 65(2):626-634, 2009.
9. Matthias Schmid and Torsten Hothorn. Boosting additive models using component-wise P-splines as base-learners. Computational Statistics & Data Analysis, 53(2):298-311, 2008.
10. Simon Urbanek. multicore: Parallel Processing of R Code on Machines with Multiple Cores or CPUs, 2009. URL http://www.rforge.net/multicore/. R package version 0.1-3.