research-learn

Toolbox to simplify the design, execution and analysis of machine learning experiments. It based on statsmodels, scikit-learn and imbalanced-learn.

Documentation

Installation documentation, API documentation, and examples can be found on the documentation.

Dependencies

research-learn is tested to work under Python 3.6+. The dependencies are the following:

• numpy(>=1.1)
• statsmodels(>=0.9.0)
• scikit-learn(>=0.22)
• imbalanced-learn(>=0.6.0)

Additionally, to run the examples, you need matplotlib(>=2.0.0) and pandas(>=0.22).

Installation

research-learn is currently available on the PyPi's repository and you can install it via pip:

pip install -U research-learn

The package is released also in Anaconda Cloud platform:

conda install -c gdouzas research-learn

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/georgedouzas/research-learn.git
cd research-learn
pip install .

Or install using pip and GitHub:

pip install -U git+https://github.com/georgedouzas/research-learn.git

Testing

After installation, you can use pytest to run the test suite:

make test