Abstract
A lot of Machine Learning (ML) and Deep Learning (DL) research is of anempirical nature. Nevertheless, statistical significance testing (SST) is still notwidely used. This endangers true progress, as seeming improvements over abaseline might be statistical flukes, leading follow-up research astray while wastinghuman and computational resources. Here, we provide an easy-to-use packagecontaining different significance tests and utility functions specifically tailoredtowards research needs and usability
| Original language | English |
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| Publication date | 2022 |
| Number of pages | 20 |
| Publication status | Published - 2022 |
| Event | ML Evaluation Standards Workshop at the Tenth International Conference on Learning Representations - Virtual Event Duration: 25 Apr 2022 → 29 Apr 2022 |
Workshop
| Workshop | ML Evaluation Standards Workshop at the Tenth International Conference on Learning Representations |
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| Location | Virtual Event |
| Period | 25/04/2022 → 29/04/2022 |