780 B
780 B
xgboost
Creater: Tianqi Chen: tianqi.tchen AT gmail
General Purpose Gradient Boosting Library
Goal: A stand-alone efficient library to do learning via boosting in functional space
Planned key components:
(1) Gradient boosting models: - regression tree - linear model/lasso (2) Objectives to support tasks: - regression - classification - ranking - matrix factorization - structured prediction (3) OpenMP implementation(optional)
File extension convention: (1) .h are interface, utils anddata structures, with detailed comment; (2) .cpp are implementations that will be compiled, with less comment; (3) .hpp are implementations that will be included by .cpp, with less comment
Parameters Usage: https://github.com/tqchen/xgboost/wiki