imbalanced-learn 0.12.4

Toolbox for imbalanced dataset in machine learning.

Stars: 6819, Watchers: 6819, Forks: 1279, Open Issues: 46

The scikit-learn-contrib/imbalanced-learn repo was created 10 years ago and the last code push was 6 days ago.
The project is extremely popular with a mindblowing 6819 github stars!

How to Install imbalanced-learn

You can install imbalanced-learn using pip

pip install imbalanced-learn

or add it to a project with poetry

poetry add imbalanced-learn

Package Details

Author

None

License

MIT

Homepage

https://github.com/scikit-learn-contrib/imbalanced-learn

PyPi:

https://pypi.org/project/imbalanced-learn/

GitHub Repo:

https://github.com/scikit-learn-contrib/imbalanced-learn

Classifiers

• Scientific/Engineering
• Software Development

Related Packages

Errors

A list of common imbalanced-learn errors.

Code Examples

Here are some imbalanced-learn code examples and snippets.

GitHub Issues

The imbalanced-learn package has 46 open issues on GitHub

• API duck-typing for n_neighbors in CNN and deprecate estimator_
• Please add a metric option like dtw or eucliedian distance metric while doing undersampling.If dtw metric is there it can be used in timeseries as well.
• Pipeline performs SMOTE both over train and validation sets
• [MRG] ENH: Geometric-SMOTE implementation
• [ENH] Add Geometric-SMOTE to imbalanced-learn
• [BUG]- error with SMOTENC fit_resample: ValueError: could not broadcast input array from shape (137,12) into shape (272,12
• [ENH] Wrapper to combine any Over Sampler and Under Sampler

See more issues on GitHub