What it does
In many datasets one group is rare, such as fraud cases among normal payments. Models trained on such data often ignore the rare group.
imbalanced-learn offers re-sampling techniques that rebalance the data, for example by adding or removing examples. It works alongside the popular scikit-learn library.
Who it's for
Data scientists training models on lopsided data.
Can I use it without coding?
Developers only. It is a Python library used in code. New to this? Start here.
Can I run it?
- Cost
- FreeNothing to pay or sign up for.
- Runs on
- Mac, Windows, Linux
- Computer
- An ordinary computer is fine
- Privacy
- Runs on your own device: your data stays with you
- API key
- Not needed
Try it
Using Claude Code, Cursor or another AI coding assistant? Paste the prompt and it will walk you through the setup.New to this?
Before you install
- Only download from the official GitHub page. Copies with similar names exist for many popular projects.
- License (MIT): Very permissive: free to use, change and share, including for business.
- More on staying safe