OpenML-CTR23 - A Curated Tabular Regression Benchmarking Suite

MCML Authors

Sebastian Fischer

→ Group Bernd Bischl
 Statistical Learning and Data Science

Matthias Feurer

Prof. Dr.

Thomas Bayes Fellow

* Former Thomas Bayes Fellow

Bernd Bischl

Prof. Dr.

Director

Statistical Learning and Data Science

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 FHF+23

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Workshop @AutoML 2023

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

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Authors

S. F. Fischer • L. Harutyunyan • M. Feurer • B. Bischl

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Links

URL

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Research Area

 A1 | Statistical Foundations & Explainability