Source: xgboost
Section: python
Priority: optional
Maintainer: Benjamin Moody <benjamin@physionet.org>
Standards-Version: 3.9.8
Build-Depends: debhelper (>= 9),
               dh-python,
               python-all,
               python-setuptools,
               python3-all,
               python3-setuptools

Package: python-xgboost
Architecture: any
Depends: ${python:Depends}, ${shlibs:Depends}, ${misc:Depends}
Description: scalable, distributed gradient boosting library (Python 2)
 XGBoost is an optimized distributed gradient boosting library
 designed to be highly efficient, flexible and portable. It implements
 machine learning algorithms under the Gradient Boosting
 framework. XGBoost provides a parallel tree boosting (also known as
 GBDT, GBM) that solve many data science problems in a fast and
 accurate way. The same code runs on major distributed environment
 (Hadoop, SGE, MPI) and can solve problems beyond billions of
 examples.
 .
 This package provides the xgboost library for Python 2.

Package: python3-xgboost
Architecture: any
Depends: python, ${python3:Depends}, ${shlibs:Depends}, ${misc:Depends}
Description: scalable, distributed gradient boosting library (Python 3)
 XGBoost is an optimized distributed gradient boosting library
 designed to be highly efficient, flexible and portable. It implements
 machine learning algorithms under the Gradient Boosting
 framework. XGBoost provides a parallel tree boosting (also known as
 GBDT, GBM) that solve many data science problems in a fast and
 accurate way. The same code runs on major distributed environment
 (Hadoop, SGE, MPI) and can solve problems beyond billions of
 examples.
 .
 This package provides the xgboost library for Python 3.
