49 citations · 70 across the 5 of their papers we have counts for
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stat.ML2024★ 3 cited
Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications
Christina Sauer, Anne-Laure Boulesteix, Luzia Hanßum +3
Adequately generating and evaluating prediction models based on supervised machine learning (ML) is often challenging, especially for less experienced users in applied research are…
stat.ML2021★ 49 cited
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
Bernd Bischl, Martin Binder, Michel Lang +9
Most machine learning algorithms are configured by one or several hyperparameters that must be carefully chosen and often considerably impact performance. To avoid a time consuming…