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 SĂĄnchez, Juan Ăngel
* GĂĄmez MartĂn, JosĂ© Antonio
License
This project is licensed under the MIT License - see the LICENSE file for details.