scikit-lr 0.2.0

A set of Python modules for Label Ranking problems.

scikit-lr

scikit-lr is a Python module integrating Machine Learning algorithms for Label Ranking problems and distributed under MIT license.

Installation

Dependencies

scikit-lr requires:

* Python>=3.6
* Numpy>=1.15.2
* SciPy>=1.1.0

Linux or Mac OS X operating systems. Windows is not currently supported.

User installation

The easiest way to install scikit-lr is using pip package:

pip install -U scikit-lr

Development

Feel free to contribute to the package, but be sure that the standards are followed.

Source code

The latest sources can be obtained with the command:

git clone https://github.com/alfaro96/scikit-lr.git

Setting up a development environment

To setup the development environment, it is strongly recommended to use docker tools (see https://github.com/alfaro96/docker-scikit-lr for details).

Alternatively, one can use Python virtual environments (see https://docs.python.org/3/library/venv.html for details).

Testing

After installation the test suite can be executed from outside the source directory, with (you will need to have pytest>=4.6.4 installed):

pytest sklr

Authors

* Alfaro Jiménez, Juan Carlos
* Aledo Sánchez, Juan Ángel
* Gámez Martín, José Antonio

License

This project is licensed under the MIT License - see the LICENSE file for details.