imbalanced-learn
The imbalanced-learn documentation explains tools for learning from imbalanced datasets in Python.
About imbalanced-learn
imbalanced-learn, imported in Python as imblearn, is an MIT-licensed library that provides tools for classification with imbalanced classes and relies on scikit-learn. Its documentation for version 0.14.2 covers installation, key concepts with background explanation, API method parameters, and a gallery of examples.
Key features
- Provides tools for classification with imbalanced classes
- Builds on scikit-learn, imported as sklearn
Best for: Python developers using scikit-learn for classification with imbalanced classes benefit most.
Good for
- MIT-licensed open source library
- Builds on scikit-learn
- Documents key concepts with background explanation and examples
imbalanced-learn at a glance
- Website
- imbalanced-learn.org/stable
- Category
- Development › Developer Tools
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for Developer Tools
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imbalanced-learn FAQ
How is imbalanced-learn imported in Python?
It is imported as imblearn.
What does imbalanced-learn rely on?
It relies on scikit-learn, imported as sklearn.
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