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 and data 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

See also: https://github.com/tqchen/xgboost/wiki