# PyMOReg: Multi-Output Regression in Python
This library contains algorithms used to perform regression on multiple (correlated) outputs simultaneously.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. As of now this is only a prototype and only the dev version is available.
### Prerequisites
To run this software you need several libraries:
- numpy >= 1.13
- scipy >= 0.19.1
- networkx >= 1.11
- scikit-learn >= 0.19.0
- matplotlib >= 2.0.2
- pandas >= 0.20.3
- seaborn >= 0.8
- pygraphviz >= 1.3.1
### Installing
These libraries come with the Anaconda bundle (www.anaconda.com) and for Linux users can be obtained by calling:
`
<sudo> apt-get install anaconda
`
In case of Windows users an .exe installer is avalailable at (www.anaconda.com/download/). For a manual install of each library the user can execute:
``` conda install <library>
``` or for cases when libraries are not available through the conda channel:
`
pip install <library>
`
Once these dependencies are installed the library can be cloned from the GitHub repository:
`
git clone https://github.com/mllera14/multi-output-regression <destination-folder>
`
To install it open a console in <destination-folder> and type:
`
python setup.py install
`
The library can now be imported into any development enviornment as:
`
import pymoreg as mreg
`
## Authors
- Milton Llera - Computational Intelligence Group, Universidad Politecnica de Madrid - [mllera14](https://github.com/mllera14)
## License
This project is licensed under the MIT License - see the [LICENSE.txt](LICENSE.txt) file for details