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Anne-Laure Boulesteix
Anne-Laure Boulesteix
Adresse e-mail validée de ibe.med.uni-muenchen.de
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Année
Bias in random forest variable importance measures: Illustrations, sources and a solution
C Strobl, AL Boulesteix, A Zeileis, T Hothorn
BMC bioinformatics 8, 1-21, 2007
37102007
Conditional variable importance for random forests
C Strobl, AL Boulesteix, T Kneib, T Augustin, A Zeileis
BMC bioinformatics 9, 1-11, 2008
32692008
Hyperparameters and tuning strategies for random forest
P Probst, MN Wright, AL Boulesteix
Wiley Interdisciplinary Reviews: data mining and knowledge discovery 9 (3 …, 2019
13532019
Partial least squares: a versatile tool for the analysis of high-dimensional genomic data
AL Boulesteix, K Strimmer
Briefings in bioinformatics 8 (1), 32-44, 2007
9192007
Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics
AL Boulesteix, S Janitza, J Kruppa, IR König
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (6 …, 2012
9182012
Tunability: Importance of hyperparameters of machine learning algorithms
P Probst, AL Boulesteix, B Bischl
Journal of Machine Learning Research 20 (53), 1-32, 2019
7252019
Random forest versus logistic regression: a large-scale benchmark experiment
R Couronné, P Probst, AL Boulesteix
BMC bioinformatics 19, 1-14, 2018
6462018
To tune or not to tune the number of trees in random forest
P Probst, AL Boulesteix
Journal of Machine Learning Research 18 (181), 1-18, 2018
4812018
Unbiased split selection for classification trees based on the Gini index
C Strobl, AL Boulesteix, T Augustin
Computational Statistics & Data Analysis 52 (1), 483-501, 2007
3612007
PLS dimension reduction for classification with microarray data
AL Boulesteix
Statistical Applications in Genetics and Molecular Biology 3 (1), 2004
2902004
Regularized estimation of large-scale gene association networks using graphical Gaussian models
N Krämer, J Schäfer, AL Boulesteix
BMC bioinformatics 10, 1-24, 2009
2682009
An AUC-based permutation variable importance measure for random forests
S Janitza, C Strobl, AL Boulesteix
BMC bioinformatics 14, 1-11, 2013
2612013
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges
B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ...
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (2 …, 2023
2452023
Stability and aggregation of ranked gene lists
AL Boulesteix, M Slawski
Briefings in bioinformatics 10 (5), 556-568, 2009
2342009
NetCoMi: network construction and comparison for microbiome data in R
S Peschel, CL Müller, E Von Mutius, AL Boulesteix, M Depner
Briefings in bioinformatics 22 (4), bbaa290, 2021
2162021
Microarray-based prediction of tumor response to neoadjuvant radiochemotherapy of patients with locally advanced rectal cancer
C Rimkus, J Friederichs, A Boulesteix, J Theisen, J Mages, K Becker, ...
Clinical gastroenterology and hepatology 6 (1), 53-61, 2008
2162008
A computationally fast variable importance test for random forests for high-dimensional data
S Janitza, E Celik, AL Boulesteix
Advances in Data Analysis and Classification 12 (4), 885-915, 2018
2032018
Random forest for ordinal responses: prediction and variable selection
S Janitza, G Tutz, AL Boulesteix
Computational Statistics & Data Analysis 96, 57-73, 2016
1922016
Survival prediction using gene expression data: a review and comparison
WN Van Wieringen, D Kun, R Hampel, AL Boulesteix
Computational statistics & data analysis 53 (5), 1590-1603, 2009
1712009
Predicting transcription factor activities from combined analysis of microarray and ChIP data: a partial least squares approach
AL Boulesteix, K Strimmer
Theoretical Biology and Medical Modelling 2, 1-12, 2005
1682005
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