| 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 | 3991 | 2007 |
| Conditional variable importance for random forests C Strobl, AL Boulesteix, T Kneib, T Augustin, A Zeileis BMC bioinformatics 9, 1-11, 2008 | 3534 | 2008 |
| Hyperparameters and tuning strategies for random forest P Probst, MN Wright, AL Boulesteix Wiley Interdisciplinary Reviews: data mining and knowledge discovery 9 (3 …, 2019 | 1787 | 2019 |
| 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 | 1027 | 2012 |
| 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 | 981 | 2007 |
| Tunability: Importance of hyperparameters of machine learning algorithms P Probst, AL Boulesteix, B Bischl Journal of Machine Learning Research 20 (53), 1-32, 2019 | 921 | 2019 |
| Random forest versus logistic regression: a large-scale benchmark experiment R Couronné, P Probst, AL Boulesteix BMC bioinformatics 19, 1-14, 2018 | 790 | 2018 |
| 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 | 581 | 2018 |
| 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 | 493 | 2023 |
| 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 | 390 | 2007 |
| 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 | 295 | 2021 |
| PLS dimension reduction for classification with microarray data AL Boulesteix Statistical Applications in Genetics and Molecular Biology 3 (1), 2004 | 294 | 2004 |
| An AUC-based permutation variable importance measure for random forests S Janitza, C Strobl, AL Boulesteix BMC bioinformatics 14, 1-11, 2013 | 288 | 2013 |
| Regularized estimation of large-scale gene association networks using graphical Gaussian models N Krämer, J Schäfer, AL Boulesteix BMC bioinformatics 10, 1-24, 2009 | 283 | 2009 |
| 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 | 240 | 2018 |
| Stability and aggregation of ranked gene lists AL Boulesteix, M Slawski Briefings in bioinformatics 10 (5), 556-568, 2009 | 235 | 2009 |
| Random forest for ordinal responses: prediction and variable selection S Janitza, G Tutz, AL Boulesteix Computational Statistics & Data Analysis 96, 57-73, 2016 | 225 | 2016 |
| 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 | 219 | 2008 |
| 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 | 177 | 2009 |
| 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 | 172 | 2005 |
