I'm looking for imbalanced classification datasets to experiment with using synthetic data, ideally with a minor class of less than 10%. Does anyone know specific ones? Should be open to the public with no limitation of use.
Most multi-class datasets can be turned into skewed binary classification datasets.
For example, the default scikit-learn digits dataset contains ~10%
1 and ~90%
That being said, the UCI Machine Learning Repository hosts many datasets that are skewed, one that's quite skewed is this SMS spam dataset: https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection
Another organisation that hosts free but not open datasets is kaggle, one of their datasets that's very skewed is the following:
Also found this one: https://www.kaggle.com/mlg-ulb/creditcardfraud - also taken from Kaggle.