I'm looking for imbalanced classification datasets to experiment with using synthetic data, ideally with a minor class of less than 10%. Anyone know specific ones? Should be open to the public with no limitation of use. Thanks!

up vote 3 down vote accepted

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% not-1 images.

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:
https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge

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    its not open data if you have to register, agree to terms, and give your phone number for verification. – albert Jul 12 at 16:19
  • This specific dataset should be open as it consists of Wikipedia comments, however, I'll verify and possibly correct when I get home. – Swier Jul 12 at 16:46
  • that process i described is this specific dataset on kaggle – albert Jul 12 at 19:25
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    @albert you're right, I've added a similar open dataset. – Swier Jul 13 at 8:30

Also found this one: https://www.kaggle.com/mlg-ulb/creditcardfraud - also taken from Kaggle.

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