These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

186 related articles for article (PubMed ID: 25112429)

  • 1. Extending statistical boosting. An overview of recent methodological developments.
    Mayr A; Binder H; Gefeller O; Schmid M
    Methods Inf Med; 2014; 53(6):428-35. PubMed ID: 25112429
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The evolution of boosting algorithms. From machine learning to statistical modelling.
    Mayr A; Binder H; Gefeller O; Schmid M
    Methods Inf Med; 2014; 53(6):419-27. PubMed ID: 25112367
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Boosting - an unusual yet attractive optimiser.
    Hothorn T
    Methods Inf Med; 2014; 53(6):417-8. PubMed ID: 25450534
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An Update on Statistical Boosting in Biomedicine.
    Mayr A; Hofner B; Waldmann E; Hepp T; Meyer S; Gefeller O
    Comput Math Methods Med; 2017; 2017():6083072. PubMed ID: 28831290
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Discussion of "the evolution of boosting algorithms" and "extending statistical boosting".
    Bühlmann P; Gertheiss J; Hieke S; Kneib T; Ma S; Schumacher M; Tutz G; Wang CY; Wang Z; Ziegler A
    Methods Inf Med; 2014; 53(6):436-45. PubMed ID: 25396219
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The importance of knowing when to stop. A sequential stopping rule for component-wise gradient boosting.
    Mayr A; Hofner B; Schmid M
    Methods Inf Med; 2012; 51(2):178-86. PubMed ID: 22344292
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Gradient boosting for linear mixed models.
    Griesbach C; Säfken B; Waldmann E
    Int J Biostat; 2021 Jan; 17(2):317-329. PubMed ID: 34826371
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Randomized boosting with multivariable base-learners for high-dimensional variable selection and prediction.
    Staerk C; Mayr A
    BMC Bioinformatics; 2021 Sep; 22(1):441. PubMed ID: 34530737
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Boosting multi-state models.
    Reulen H; Kneib T
    Lifetime Data Anal; 2016 Apr; 22(2):241-62. PubMed ID: 25990764
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Approaches to Regularized Regression - A Comparison between Gradient Boosting and the Lasso.
    Hepp T; Schmid M; Gefeller O; Waldmann E; Mayr A
    Methods Inf Med; 2016 Oct; 55(5):422-430. PubMed ID: 27626931
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Boosting the discriminatory power of sparse survival models via optimization of the concordance index and stability selection.
    Mayr A; Hofner B; Schmid M
    BMC Bioinformatics; 2016 Jul; 17():288. PubMed ID: 27444890
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Flexible boosting of accelerated failure time models.
    Schmid M; Hothorn T
    BMC Bioinformatics; 2008 Jun; 9():269. PubMed ID: 18538026
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Boosting regression estimators.
    Avnimelech R; Intrator N
    Neural Comput; 1999 Feb; 11(2):499-520. PubMed ID: 9950741
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Boosting joint models for longitudinal and time-to-event data.
    Waldmann E; Taylor-Robinson D; Klein N; Kneib T; Pressler T; Schmid M; Mayr A
    Biom J; 2017 Nov; 59(6):1104-1121. PubMed ID: 28321912
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Regularization for generalized additive mixed models by likelihood-based boosting.
    Groll A; Tutz G
    Methods Inf Med; 2012; 51(2):168-77. PubMed ID: 22378253
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Stochastic approximation boosting for incomplete data problems.
    Sexton J; Laake P
    Biometrics; 2009 Dec; 65(4):1156-63. PubMed ID: 19432768
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Generalized additive modeling with implicit variable selection by likelihood-based boosting.
    Tutz G; Binder H
    Biometrics; 2006 Dec; 62(4):961-71. PubMed ID: 17156269
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Joint Modelling Approaches to Survival Analysis via Likelihood-Based Boosting Techniques.
    Griesbach C; Groll A; Bergherr E
    Comput Math Methods Med; 2021; 2021():4384035. PubMed ID: 34819988
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Robust statistical boosting with quantile-based adaptive loss functions.
    Speller J; Staerk C; Mayr A
    Int J Biostat; 2023 May; 19(1):111-129. PubMed ID: 35950232
    [TBL] [Abstract][Full Text] [Related]  

  • 20. The betaboost package-a software tool for modelling bounded outcome variables in potentially high-dimensional epidemiological data.
    Mayr A; Weinhold L; Hofner B; Titze S; Gefeller O; Schmid M
    Int J Epidemiol; 2018 Oct; 47(5):1383-1388. PubMed ID: 30380092
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.