Contents

imbalanced-learn 0.11.0

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Toolbox for imbalanced dataset in machine learning.

Toolbox for imbalanced dataset in machine learning.

Stars: 6435, Watchers: 6435, Forks: 1246, Open Issues: 35

The scikit-learn-contrib/imbalanced-learn repo was created 8 years ago and the last code push was 1 weeks ago.
The project is extremely popular with a mindblowing 6435 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
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
No  imbalanced-learn  pypi packages just yet.

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 35 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

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