imbalanced-ensemble
Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.
About imbalanced-ensemble
IMBENS (imported as imbens) is an open-source Python library for implementing, evaluating, and comparing methods for classification when class sizes are uneven. The source describes it as covering more than 30 algorithms, including under-sampling, over-sampling such as SMOTE and its variants, cost-sensitive learning such as AdaCost, and ensemble methods such as SMOTEBagging, RUSBoost, and SelfPacedEnsemble.
The library follows scikit-learn design principles and was originally built on imbalanced-learn, but the source states that it has since developed independently and no longer depends on it. Users can combine it with scikit-learn utilities for data processing, cross-validation, and hyperparameter tuning. Installation is recommended through pip, and the source lists several required dependencies, including scikit-learn 1.2.0 or later.
Key features
- Over 30 algorithms for class-imbalanced classification
- Under-sampling, over-sampling, and cost-sensitive learning methods
- Ensemble methods such as SMOTEBagging, RUSBoost, and SelfPacedEnsemble
- Scikit-learn-style APIs for fitting and prediction
- Parallelization using joblib for training efficiency
- Benchmarking and comparison of multiple models with a visualizer
Best for: Python developers and researchers who build classification models on imbalanced datasets and already use or want to use scikit-learn.
Good for
- Uses scikit-learn-style APIs, which the source describes as unified and user-friendly
- Extends several binary imbalance techniques to the multi-class setting
- Open source, with documentation and examples in the repository
Watch out for
- Requires a Python environment with several listed dependencies, including scikit-learn 1.2.0 or later
imbalanced-ensemble at a glance
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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imbalanced-ensemble FAQ
How is imbalanced-ensemble installed?
The source recommends pip. The command is pip install imbalanced-ensemble, and pip install --upgrade imbalanced-ensemble can be used to update it. It can also be installed by cloning the repository and running pip install .
What name is used when importing the package?
The package is imported as imbens, for example from imbens.ensemble import SelfPacedEnsembleClassifier.
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