* Make train in xgboost4j respect print params Previously no setting in params argument of Booster::train would prevent the Rabit.trackerPrint call. This can fill up a lot of screen space in the case that many folds are being trained. * Setting "silent" in this map to "true", "True", a non-zero integer, or a string that can be parsed to such an int will prevent printing. * Setting "verbose_eval" to "False" or "false" will prevent printing. * Setting "verbose_eval" to an int (or a String parseable to an int) n will result in printing every n steps, or no printing is n is zero. This is to match the python behaviour described here: https://www.kaggle.com/c/rossmann-store-sales/discussion/17499 * Fixed 'slient' typo in xgboost4j test * private access on two methods
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.

