The project has been moved to imbalanced-learn-extra.
Category | Tools |
---|---|
Development | |
Package | |
Documentation | |
Communication |
The package geometric-smote
implements the Geometric SMOTE algorithm, a geometrically enhanced drop-in replacement for SMOTE. It
is compatible with scikit-learn and imbalanced-learn. The Geometric SMOTE algorithm can handle numerical as well as categorical
features.
For user installation, geometric-smote
is currently available on the PyPi's repository, and you can
install it via pip
:
pip install geometric-smote
Development installation requires cloning the repository and then using PDM to install the project as well as the main and development dependencies:
git clone https://github.com/georgedouzas/geometric-smote.git
cd geometric-smote
pdm install
All the classes included in geometric-smote
follow the imbalanced-learn API using the
functionality of the base oversampler. Using scikit-learn convention, the data are represented
as follows:
- Input data
X
: 2D array-like or sparse matrices. - Targets
y
: 1D array-like.
The clustering-based oversamplers implement a fit
method to learn from X
and y
:
gsmote_oversampler.fit(X, y)
They also implement a fit_resample
method to resample X
and y
:
X_resampled, y_resampled = gsmote.fit_resample(X, y)
If you use geometric-smote
in a scientific publication, we would appreciate citations to the following paper:
- Douzas, G., Bacao, B. (2019). Geometric SMOTE: a geometrically enhanced drop-in replacement for SMOTE. Information Sciences, 501, 118-135. https://doi.org/10.1016/j.ins.2019.06.007
Publications using Geometric-SMOTE:
-
Fonseca, J., Douzas, G., Bacao, F. (2021). Increasing the Effectiveness of Active Learning: Introducing Artificial Data Generation in Active Learning for Land Use/Land Cover Classification. Remote Sensing, 13(13), 2619. https://doi.org/10.3390/rs13132619
-
Douzas, G., Bacao, F., Fonseca, J., Khudinyan, M. (2019). Imbalanced Learning in Land Cover Classification: Improving Minority Classes’ Prediction Accuracy Using the Geometric SMOTE Algorithm. Remote Sensing, 11(24), 3040. https://doi.org/10.3390/rs11243040