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.
Installed Size: 55.3 kB
Architectures: all