Pakket: libxgboost-dev (1.7.4-1)

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.

This page is also available in the following languages (How to set the default document language):