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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.02200 |
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| _version_ | 1866914810986233856 |
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| author | Herrmann, Moritz Lange, F. Julian D. Eggensperger, Katharina Casalicchio, Giuseppe Wever, Marcel Feurer, Matthias Rügamer, David Hüllermeier, Eyke Boulesteix, Anne-Laure Bischl, Bernd |
| author_facet | Herrmann, Moritz Lange, F. Julian D. Eggensperger, Katharina Casalicchio, Giuseppe Wever, Marcel Feurer, Matthias Rügamer, David Hüllermeier, Eyke Boulesteix, Anne-Laure Bischl, Bernd |
| contents | 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 undermine progress in the field. To overcome this alarming situation, we call for more awareness of the plurality of ways of gaining knowledge experimentally but also of some epistemic limitations. In particular, we argue most current empirical machine learning research is fashioned as confirmatory research while it should rather be considered exploratory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_02200 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Position: Why We Must Rethink Empirical Research in Machine Learning Herrmann, Moritz Lange, F. Julian D. Eggensperger, Katharina Casalicchio, Giuseppe Wever, Marcel Feurer, Matthias Rügamer, David Hüllermeier, Eyke Boulesteix, Anne-Laure Bischl, Bernd Machine Learning 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 undermine progress in the field. To overcome this alarming situation, we call for more awareness of the plurality of ways of gaining knowledge experimentally but also of some epistemic limitations. In particular, we argue most current empirical machine learning research is fashioned as confirmatory research while it should rather be considered exploratory. |
| title | Position: Why We Must Rethink Empirical Research in Machine Learning |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2405.02200 |