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mlr3pipelines - Flexible Machine Learning Pipelines in R., , , , , und . J. Mach. Learn. Res., (2021)Statistical analysis of extreme events in a non-stationary context via a Bayesian framework: case study with peak-over-threshold data, , und . Stochastic Environmental Research and Risk Assessment, (2006)A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data., , und . Comput. Math. Methods Medicine, (2017)Development of regional flood-duration-frequency curves based on the index-flood method, , , , , und . Journal of Hydrology, 258 (1-4): 249 - 259 (2002)Employing an Adjusted Stability Measure for Multi-criteria Model Fitting on Data Sets with Similar Features., , und . LOD, Volume 13163 von Lecture Notes in Computer Science, Seite 81-92. Springer, (2021)mlrMBO: A modular framework for model-based optimization of expensive black-box functions, , , , , und . arXiv preprint arXiv:1703.03373, (2017)BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments, , , , und . Journal of Statistical Software, (März 2015)Model-based optimization with concept drifts., , , , und . GECCO, Seite 877-885. ACM, (2020)Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges, , , , , , , , , und 2 andere Autor(en). Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, (10.03.2023)Funding Information: Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology, Grant/Award Number: BAYERN DIGITAL II; Bundesministerium für Bildung und Forschung, Grant/Award Number: 01IS18036A; Deutsche Forschungsgemeinschaft (Collaborative Research Center), Grant/Award Number: SFB 876‐A3; Federal Statistical Office of Germany; Research Center “Trustworthy Data Science and Security” Funding information Funding Information: The authors of this work take full responsibilities for its content. This work was supported by the Federal Statistical Office of Germany; the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876, A3; the Research Center “Trustworthy Data Science and Security”, one of the Research Alliance centers within the https://uaruhr.de ; the German Federal Ministry of Education and Research (BMBF) under Grant No. 01IS18036A; and the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics‐Data‐Applications (ADA‐Center) within the framework of “BAYERN DIGITAL II.”.OpenML Benchmarking Suites., , , , , , , , und . NeurIPS Datasets and Benchmarks, (2021)