Anne-Laure Boulesteix

67 papers A* 1Journal 64

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Overcoming Barriers to Computational Reproducibility. CoRR Roman Hornung, László Németh, Oleksandr Zadorozhny, Theresa Ullmann, Michael Kammer, Rebecca Killick, Christopher J. Paciorek, Julien Chiquet, Moritz Herrmann, Lucija Batinovíc, Rickard Carlsson, Pierre Neuvial, Boris P. Hejblum, Julia Wrobel, Anne-Laure Boulesteix, Karsten Tabelow
2025	J	`jnl`	Comparing supervised machine learning algorithms for the prediction of partial arterial pressure of oxygen during craniotomy. BMC Medical Informatics Decis. Mak. Andrea S. Gutmann, Maximilian M. Mandl, Clemens Rieder, Dominik J. Hoechter, Konstantin Dietz, Benjamin P. Geisler, Anne-Laure Boulesteix, Roland Tomasi, Ludwig Christian G. Hinske
2025	J	`jnl`	Constructing Confidence Intervals for “the” Generalization Error – a Comprehensive Benchmark Study. J. Data-centric Mach. Learn. Res. Hannah Schulz-Kümpel, Sebastian Fischer, Roman Hornung, Anne-Laure Boulesteix, Thomas Nagler, Bernd Bischl
2024	J	`jnl`	Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications. CoRR Christina Sauer, Anne-Laure Boulesteix, Luzia Hanßum, Farina Hodiamont, Claudia Bausewein, Theresa Ullmann
2024	J	`jnl`	Constructing Confidence Intervals for 'the' Generalization Error - a Comprehensive Benchmark Study. CoRR Hannah Schulz-Kümpel, Sebastian Fischer, Thomas Nagler, Anne-Laure Boulesteix, Bernd Bischl, Roman Hornung
2024	A*	`conf`	Position: Why We Must Rethink Empirical Research in Machine Learning. ICML Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	J	`jnl`	Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	J	`jnl`	Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices. PLoS Comput. Biol. Maximilian M. Mandl, Sabine Hoffmann, Sebastian Bieringer, Anna E. Jacob, Marie Kraft, Simon Lemster, Anne-Laure Boulesteix
2024	J	`jnl`	Understanding random forests and overfitting: a visualization and simulation study. CoRR Lasai Barreñada, Paula Dhiman, Dirk Timmerman, Anne-Laure Boulesteix, Ben Van Calster
2023	J	`jnl`	A white paper on good research practices in benchmarking: The case of cluster analysis. WIREs Data. Mining. Knowl. Discov. Iven Van Mechelen, Anne-Laure Boulesteix, Rainer Dangl, Nema Dean, Christian Hennig, Friedrich Leisch, Douglas L. Steinley, Matthijs J. Warrens
2023	J	`jnl`	Evaluating machine learning models in non-standard settings: An overview and new findings. CoRR Roman Hornung, Malte Nalenz, Lennart Schneider, Andreas Bender, Ludwig Bothmann, Bernd Bischl, Thomas Augustin, Anne-Laure Boulesteix
2023	J	`jnl`	Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges. WIREs Data. Mining. Knowl. Discov. Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer
2023	J	`jnl`	Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering. PLoS Comput. Biol. Theresa Ullmann, Stefanie Peschel, Philipp F. M. Baumann, Christian L. Müller, Anne-Laure Boulesteix
2023	J	`jnl`	Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study. Adv. Data Anal. Classif. Theresa Ullmann, Anna Beer, Maximilian Hünemörder, Thomas Seidl, Anne-Laure Boulesteix
2023	J	`jnl`	Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study. CoRR Roman Hornung, Frederik Ludwigs, Jonas Hagenberg, Anne-Laure Boulesteix
2022	J	`jnl`	Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects. Comput. Stat. Data Anal. Roman Hornung, Anne-Laure Boulesteix
2022	J	`jnl`	Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results. WIREs Data Mining Knowl. Discov. Christina Nießl, Moritz Herrmann, Chiara Wiedemann, Giuseppe Casalicchio, Anne-Laure Boulesteix
2022	J	`jnl`	Validation of cluster analysis results on validation data: A systematic framework. WIREs Data Mining Knowl. Discov. Theresa Ullmann, Christian Hennig, Anne-Laure Boulesteix
2021	J	`jnl`	Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges. CoRR Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer
2021	J	`jnl`	Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning. J. Classif. Nicole Ellenbach, Anne-Laure Boulesteix, Bernd Bischl, Kristian Unger, Roman Hornung
2021	J	`jnl`	Large-scale benchmark study of survival prediction methods using multi-omics data. Briefings Bioinform. Moritz Herrmann, Philipp Probst, Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix
2021	J	`jnl`	NetCoMi: network construction and comparison for microbiome data in R. Briefings Bioinform. Stefanie Peschel, Christian L. Müller, Erika von Mutius, Anne-Laure Boulesteix, Martin Depner
2020	J	`jnl`	Combining clinical and molecular data in regression prediction models: insights from a simulation study. Briefings Bioinform. Riccardo De Bin, Anne-Laure Boulesteix, Axel Benner, Natalia Becker, Willi Sauerbrei
2020	J	`jnl`	Large-scale benchmark study of survival prediction methods using multi-omics data. CoRR Moritz Herrmann, Philipp Probst, Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix
2019	J	`jnl`	Hyperparameters and tuning strategies for random forest. WIREs Data Mining Knowl. Discov. Philipp Probst, Marvin N. Wright, Anne-Laure Boulesteix
2019	J	`jnl`	Tunability: Importance of Hyperparameters of Machine Learning Algorithms. J. Mach. Learn. Res. Philipp Probst, Anne-Laure Boulesteix, Bernd Bischl
2018	J	`jnl`	A computationally fast variable importance test for random forests for high-dimensional data. Adv. Data Anal. Classif. Silke Janitza, Ender Celik, Anne-Laure Boulesteix
2018	J	`jnl`	Hyperparameters and Tuning Strategies for Random Forest. CoRR Philipp Probst, Marvin N. Wright, Anne-Laure Boulesteix
2018	J	`jnl`	On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models. Comput. Stat. Heidi Seibold, Christoph Bernau, Anne-Laure Boulesteix, Riccardo De Bin
2018	J	`jnl`	Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data. BMC Bioinform. Simon Klau, Vindi Jurinovic, Roman Hornung, Tobias Herold, Anne-Laure Boulesteix
2018	J	`jnl`	Random forest versus logistic regression: a large-scale benchmark experiment. BMC Bioinform. Raphaël Couronné, Philipp Probst, Anne-Laure Boulesteix
2017	J	`jnl`	Detection of influential points as a byproduct of resampling-based variable selection procedures. Comput. Stat. Data Anal. Riccardo De Bin, Anne-Laure Boulesteix, Willi Sauerbrei
2017	J	`jnl`	IPF-LASSO: Integrative L Comput. Math. Methods Medicine Anne-Laure Boulesteix, Riccardo De Bin, Xiaoyu Jiang, Mathias Fuchs
2017	J	`jnl`	Improving cross-study prediction through addon batch effect adjustment or addon normalization. Bioinform. Roman Hornung, David Causeur, Christoph Bernau, Anne-Laure Boulesteix
2017	J	`jnl`	To Tune or Not to Tune the Number of Trees in Random Forest. J. Mach. Learn. Res. Philipp Probst, Anne-Laure Boulesteix
2017	J	`jnl`	To tune or not to tune the number of trees in random forest? CoRR Philipp Probst, Anne-Laure Boulesteix
2016	J	`jnl`	Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment. BMC Bioinform. Roman Hornung, Anne-Laure Boulesteix, David Causeur
2016	J	`jnl`	Random forest for ordinal responses: Prediction and variable selection. Comput. Stat. Data Anal. Silke Janitza, Gerhard Tutz, Anne-Laure Boulesteix
2015	J	`jnl`	Letter to the Editor: On Reviews and Papers on New Methods. Briefings Bioinform. Anne-Laure Boulesteix
2015	J	`jnl`	Letter to the Editor: On the term 'interaction' and related phrases in the literature on Random Forests. Briefings Bioinform. Anne-Laure Boulesteix, Silke Janitza, Alexander Hapfelmeier, Kristel Van Steen, Carolin Strobl
2015	J	`jnl`	Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research. PLoS Comput. Biol. Anne-Laure Boulesteix
2014	J	`jnl`	Cross-study validation for the assessment of prediction algorithms. Bioinform. Christoph Bernau, Markus Riester, Anne-Laure Boulesteix, Giovanni Parmigiani, Curtis Huttenhower, Levi Waldron, Lorenzo Trippa
2013	J	`jnl`	An AUC-based permutation variable importance measure for random forests. BMC Bioinform. Silke Janitza, Carolin Strobl, Anne-Laure Boulesteix
2013	—	`ch.`	Complexity Selection with Cross-validation for Lasso and Sparse Partial Least Squares Using High-Dimensional Data. Algorithms from and for Nature and Life Anne-Laure Boulesteix, Adrian Richter, Christoph Bernau
2013	J	`jnl`	On representative and illustrative comparisons with real data in bioinformatics: response to the letter to the editor by Smith Bioinform. Anne-Laure Boulesteix
2013	—	`ch.`	On the Simultaneous Analysis of Clinical and Omics Data: A Comparison of Globalboosttest and Pre-validation Techniques. Statistical Models for Data Analysis Margret-Ruth Oelker, Anne-Laure Boulesteix
2012	J	`jnl`	A Plea for Neutral Comparison Studies in Computational Sciences CoRR Anne-Laure Boulesteix, Manuel J. A. Eugster
2012	J	`jnl`	Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics. WIREs Data Mining Knowl. Discov. Anne-Laure Boulesteix, Silke Janitza, Jochen Kruppa, Inke R. König
2012	J	`jnl`	Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations. Briefings Bioinform. Anne-Laure Boulesteix, Andreas Bender, Justo Lorenzo Bermejo, Carolin Strobl
2011	J	`jnl`	Added predictive value of high-throughput molecular data to clinical data and its validation. Briefings Bioinform. Anne-Laure Boulesteix, Willi Sauerbrei
2011	J	`jnl`	Editorial. Briefings Bioinform. Anne-Laure Boulesteix
2010	J	`jnl`	Over-optimism in bioinformatics research. Bioinform. Anne-Laure Boulesteix
2010	J	`jnl`	Over-optimism in bioinformatics: an illustration. Bioinform. Monika Jelizarow, Vincent Guillemot, Arthur Tenenhaus, Korbinian Strimmer, Anne-Laure Boulesteix
2010	J	`jnl`	Testing the additional predictive value of high-dimensional molecular data. BMC Bioinform. Anne-Laure Boulesteix, Torsten Hothorn
2009	J	`jnl`	Regularized estimation of large-scale gene association networks using graphical Gaussian models. BMC Bioinform. Nicole Krämer, Juliane Schäfer, Anne-Laure Boulesteix
2009	J	`jnl`	Stability and aggregation of ranked gene lists. Briefings Bioinform. Anne-Laure Boulesteix, Martin Slawski
2009	J	`jnl`	Survival prediction using gene expression data: A review and comparison. Comput. Stat. Data Anal. Wessel N. van Wieringen, David Kun, Regina Hampel, Anne-Laure Boulesteix
2008	J	`jnl`	CMA - a comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinform. Martin Slawski, Martin Daumer, Anne-Laure Boulesteix
2008	J	`jnl`	Conditional variable importance for random forests. BMC Bioinform. Carolin Strobl, Anne-Laure Boulesteix, Thomas Kneib, Thomas Augustin, Achim Zeileis
2008	J	`jnl`	Microarray-based classification and clinical predictors: on combined classifiers and additional predictive value. Bioinform. Anne-Laure Boulesteix, Christine Porzelius, Martin Daumer
2007	J	`jnl`	Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinform. Carolin Strobl, Anne-Laure Boulesteix, Achim Zeileis, Torsten Hothorn
2007	J	`jnl`	Maximally selected Chi-squared statistics and non-monotonic associations: An exact approach based on two cutpoints. Comput. Stat. Data Anal. Anne-Laure Boulesteix, Carolin Strobl
2007	J	`jnl`	Partial least squares: a versatile tool for the analysis of high-dimensional genomic data. Briefings Bioinform. Anne-Laure Boulesteix, Korbinian Strimmer
2007	J	`jnl`	Unbiased split selection for classification trees based on the Gini Index. Comput. Stat. Data Anal. Carolin Strobl, Anne-Laure Boulesteix, Thomas Augustin
2007	J	`jnl`	WilcoxCV: an R package for fast variable selection in cross-validation. Bioinform. Anne-Laure Boulesteix
2006	J	`jnl`	Identification of interaction patterns and classification with applications to microarray data. Comput. Stat. Data Anal. Anne-Laure Boulesteix, Gerhard Tutz
2003	J	`jnl`	A CART-based approach to discover emerging patterns in microarray data. Bioinform. Anne-Laure Boulesteix, Gerhard Tutz, Korbinian Strimmer