Source: xgboost Section: science Homepage: https://xgboost.ai/ Priority: optional Standards-Version: 4.6.0.1 Vcs-Git: https://salsa.debian.org/deeplearning-team/xgboost.git Vcs-Browser: https://salsa.debian.org/deeplearning-team/xgboost Maintainer: Debian Deep Learning Team Uploaders: Mo Zhou Rules-Requires-Root: no Build-Depends: cmake, debhelper-compat (= 13), dh-python, libdmlc-dev (>= 0.5), python3-all, python3-setuptools Package: xgboost Architecture: any Depends: libxgboost0 (= ${binary:Version}), ${misc:Depends}, ${shlibs:Depends} Description: Scalable and Flexible Gradient Boosting (Executable) 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 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples. . This package contains the xgboost binary executable. Package: libxgboost-dev Section: libdevel Architecture: any Depends: libxgboost0 (= ${binary:Version}), ${misc:Depends} Description: Scalable and Flexible Gradient Boosting (Development) 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 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples. . This package contains the xgboost development files. Package: libxgboost0 Section: libs Architecture: any Depends: ${misc:Depends}, ${shlibs:Depends} Description: Scalable and Flexible Gradient Boosting (Shared lib) 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 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples. . This package contains the xgboost shared object. Package: python3-xgboost Section: python Architecture: any Depends: libxgboost0 (= ${binary:Version}), ${misc:Depends}, ${python3:Depends} Description: Scalable and Flexible Gradient Boosting (Python3) 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 (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples. . This package contains the xgboost python3 binding.