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OpenML-CTR23 - A Curated Tabular Regression Benchmarking Suite

MCML Authors

Matthias Feurer

Prof. Dr.

Thomas Bayes Fellow

* Former Thomas Bayes Fellow

Link to Profile Bernd Bischl PI Matchmaking

Bernd Bischl

Prof. Dr.

Director

Abstract

Benchmark experiments are one of the cornerstones of modern machine learning research. An essential part in the design of such experiments is the selection of datasets. We present the OpenML Curated Tabular Regression benchmarking suite 2023 (OpenML-CTR23). It is available on OpenML and comprises 35 regression problems that have been selected according to a set of strict criteria. We compare its design with existing regression benchmark suites and also challenge some of the dataset choices of previous efforts. As a first experiment, we compare five machine learning methods of varying complexity on the OpenML-CTR23.

inproceedings


AutoML 2023 - Workshop Track

International Conference on Automated Machine Learning - Workshop Track. Berlin, Germany, Sep 12-15, 2023.

Authors

S. F. Fischer • L. Harutyunyan • M. FeurerB. Bischl

Links

URL

Research Area

 A1 | Statistical Foundations & Explainability

BibTeXKey: FHF+23

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