Abstract
A gradient-descent boosting algorithm is presented for survival time data, where the individual additive components are regression trees.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. (1984). Classification and Regression Trees. Wadsworth, CA
Breiman, L. (1996). Bagging predictors. Machine Learning, 24, 123–140.
Breiman, L. (1998). Arcing classifiers. Annals of Statistics, 26, 801–849.
Dietterich, T.G. (2000). An experimental comparison of three methods forconstructing ensembles of decision trees: Bagging, boosting, and randomization. Machine Learning, 40, 139–157.
Doehner, H., Stilgenbauer, S., Benner, A., Leupolt, E., Kroeber, A., Bullinger, L., Doehner, K., Bentz, M. and Lichter, P. (2000). Genomic aberrations and survival in chronic lymphocytic leukemia. New England Journal of Medicine,343, 1910–1916.
Freund, Y. and Schapire, R.E. (1996). Experiments with a new boosting algorithm. in In: Proceedings of the 13th International Conference on Machine Learning, 148–156. San Francisco, CA: Morgan Kaufmann.
Friedman, J.H. (2001). Greedy function approximation: A gradient boosting machine. Annals of Statistics, 29.
Friedman, J.H., Hastie, T. and Tibshirani, R. (2000). Additive logistic regression: A statistical view of boosting. Annals of Statistics, 28, 337–407.
Gordon, L. and Olshen, R.A.(1985). Tree-structured survival analysis (with discussion). Cancer Treatment Reports, 69, 1065–1068.
Graf, E., Schmoor, C., Sauerbrei, W. and Schumacher, M. (1999). Assessment and comparison of prognostic classification schemes for survival data. Statistics in Medicine, 18, 2529–2545.
LeBlanc, M. and Crowley, J. (1992). Relative risk trees for censored survival data. Biometrics, 48, 411–425.
LeBlanc, M. and Crowley, J. (1993). Survival trees by goodness of split. Journal of the American Statistical Association, 88, 457–467.
Segal, M.R. (1988). Regression trees for censored data. Biometrics, 44, 35–47.
Therneau, T.M. and Atkinson, E.J. (1997). An Introduction to Recursive Partitioning Using the RPART Routines. Mayo Clinic Section of Biostatistics technical report #61
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Benner, A. (2002). Application of “Aggregated Classifiers” in Survival Time Studies. In: Härdle, W., Rönz, B. (eds) Compstat. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57489-4_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-57489-4_21
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1517-7
Online ISBN: 978-3-642-57489-4
eBook Packages: Springer Book Archive