GitHub - dmlc/xgboost: Scalable, Portable and Distributed …
Community | Documentation | Resources | Contributors | Release Notes. XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It …
XGBoost
Supports multiple languages including C++, Python, R, Java, Scala, Julia. Wins many data science and machine learning challenges. Used in production by multiple companies. …
XGBoost Documentation — xgboost 0.4 documentation
The goal of this library is to push the extreme of the computation limits of machines to provide a scalable, portable and accurate for large scale tree boosting. This document is hosted at …
XGBoost - University of Washington
See XGBoost Resources Page for a complete list of usecases of XGBoost, including machine learning challenge winning solutions, data science tutorials and industry adoptions.
JSON and UBJSON have the same document structure with different representations, and we will refer them collec-tively as the JSON format. This tutorial aims to share some basic insights …
Package 'xgboost' reference manual - cran.dev
Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its …
XGBoost Tutorials — xgboost 0.90 documentation
XGBoost Tutorials ¶ This section contains official tutorials inside XGBoost package. See Awesome XGBoost for more resources.
XGBoost - Wikipedia
XGBoost[2] (eXtreme Gradient Boosting) is an open-source software library which provides a regularizing gradient boosting framework for C++, Java, Python, [3] R, [4] Julia, [5] Perl, [6] …
XGBoost API | XGBoosting
You can access the XGBoost API documentation here: The Python API documentation is available here: Got ideas? Suggest more examples to add.
xgboost documentation
Dump an XGBoost model in text format.