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Installation¶

Installation of this project is dependent on XGBoost, which has a slightly difficult installation process.

Installing XGBoost¶

Since this library depends heavily on XGBoost, we recommend following the installation instructions posted there for installing XGBoost on your system.

We use the Scikit-Learn Python wrappers for XGBoost, which do not support GPU execution at the moment, and the models themselves are trained on exceedingly small amounts of data, therefore we do not require GPU execution of XGBoost.

XGBoost : Install Instructions
Or via pip : pip install --upgrade xgboost

Windows Installation

For installation of XGBoost on Windows, it is preferred to use the unofficial binaries provided here if you do not wish to build the project yourself :

XGBoost : Unofficial Windows Binaries

Installation of PySHAC¶

Once the XGBoost package is installed and verifier, we can simply clone this repository and run python setup.py install to install this package.

git clone https://github.com/titu1994/pyshac.git
cd pyshac
pip install .

Installation of External Libraries¶

When using the managed engines, it is required to separately install external libraries such as :