Getting Started¶
Prerequisites¶
The imbalanced-learn package requires the following dependencies:
python (>=3.6)
numpy (>=1.13.3)
scipy (>=0.19.1)
scikit-learn (>=0.23)
keras 2 (optional)
tensorflow (optional)
Install¶
From PyPi or conda-forge repositories¶
imbalanced-learn is currently available on the PyPi’s repositories and you can
install it via pip:
pip install -U imbalanced-learn
The package is release also in Anaconda Cloud platform:
conda install -c conda-forge imbalanced-learn
From source available on GitHub¶
If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from Github and install all dependencies:
git clone https://github.com/scikit-learn-contrib/imbalanced-learn.git
cd imbalanced-learn
pip install .
Be aware that you can install in developer mode with:
pip install --no-build-isolation --editable .
If you wish to make pull-requests on GitHub, we advise you to install pre-commit:
pip install pre-commit
pre-commit install
Test and coverage¶
You want to test the code before to install:
$ make test
You wish to test the coverage of your version:
$ make coverage
You can also use pytest:
$ pytest imblearn -v