4d6590be3c
* Initial performance optimizations for xgboost * remove includes * revert float->double * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * Check existence of _mm_prefetch and __builtin_prefetch * Fix lint * optimizations for CPU * appling comments in review * add some comments, code refactoring * fixing issues in CI * adding runtime checks * remove 1 extra check * remove extra checks in BuildHist * remove checks * add debug info * added debug info * revert changes * added comments * Apply suggestions from code review Co-Authored-By: Philip Hyunsu Cho <chohyu01@cs.washington.edu> * apply review comments * Remove unused function CreateNewNodes() * Add descriptive comment on node_idx variable in QuantileHistMaker::Builder::BuildHistsBatch()
eXtreme Gradient Boosting
Community | Documentation | Resources | Contributors | Release Notes
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.
License
© Contributors, 2016. Licensed under an Apache-2 license.
Contribute to XGBoost
XGBoost has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone. Checkout the Community Page
Reference
- Tianqi Chen and Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. In 22nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2016
- XGBoost originates from research project at University of Washington.
Sponsors
Become a sponsor and get a logo here. See details at Sponsoring the XGBoost Project. The funds are used to defray the cost of continuous integration and testing infrastructure (https://xgboost-ci.net).
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The sponsors in this list are donating cloud hours in lieu of cash donation.
