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20062025
most citedHyperparameters and Tuning Strategies for Random Forest

1.6k citations · 3.3k across the 24 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

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.ML2024★ 4 cited

Constructing Confidence Intervals for 'the' Generalization Error -- a Comprehensive Benchmark Study

Hannah Schulz-Kümpel, Sebastian Fischer, Roman Hornung +3

When assessing the quality of prediction models in machine learning, confidence intervals (CIs) for the generalization error, which measures predictive performance, are a crucial t…

stat.ME2024★ 2 cited

Rethinking the handling of method failure in comparison studies

Milena Wünsch, Moritz Herrmann, Elisa Noltenius +3

Comparison studies in methodological research are intended to compare methods in an evidence-based manner to help data analysts select a suitable method for their application. To p…

cs.LG2024★ 2 cited

Position: Why We Must Rethink Empirical Research in Machine Learning

Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger +7

We warn against a common but incomplete understanding of empirical research in machine learning that leads to non-replicable results, makes findings unreliable, and threatens to un…

stat.ME2024★ 143 cited

Understanding overfitting in random forest for probability estimation: a visualization and simulation study

Lasai Barreñada, Paula Dhiman, Dirk Timmerman +2

Random forests have become popular for clinical risk prediction modelling. In a case study on predicting ovarian malignancy, we observed training c-statistics close to 1. Although…

stat.AP2024

To tweak or not to tweak. How exploiting flexibilities in gene set analysis leads to over-optimism

Milena Wünsch, Christina Sauer, Moritz Herrmann +2

Gene set analysis, a popular approach for analysing high-throughput gene expression data, aims to identify sets of genes that show enriched expression patterns between two conditio…

stat.ME2024★ 3 cited

Addressing researcher degrees of freedom through minP adjustment

Maximilian M Mandl, Andrea S Becker-Pennrich, Ludwig C Hinske +2

When different researchers study the same research question using the same dataset they may obtain different and potentially even conflicting results. This is because there is ofte…