Waterbirds

Dataset bias is a significant problem in training fair classifiers. When attributes unrelated to classification exhibit strong biases towards certain classes, classifiers trained on such dataset may overfit to these bias attributes, substantially reducing the accuracy for minority groups.

Data and Resources

Cite this as

Chaoquan Jiang, Jinqiang Wang, Rui Hu, Jitao Sang (2024). Dataset: Waterbirds. https://doi.org/10.57702/8n99p2cp

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2403.09869
Citation
  • https://doi.org/10.48550/arXiv.2208.02192
  • https://doi.org/10.48550/arXiv.2212.02090
  • https://doi.org/10.48550/arXiv.2406.02889
  • https://doi.org/10.48550/arXiv.2312.05588
Author Chaoquan Jiang
More Authors
Jinqiang Wang
Rui Hu
Jitao Sang
Homepage https://www.waterbirds-dataset.com/