33 lines
1.0 KiB
Markdown
33 lines
1.0 KiB
Markdown
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
|
|
|
|
Features:
|
|
(1) Sparse feature format, handling of missing features. This allows efficient categorical feature encoding as indicators. The speed of booster only depends on number of existing features.
|
|
(2) Layout of gradient boosting algorithm to support generic tasks, see project wiki.
|
|
|
|
|
|
Planned key components:
|
|
|
|
(1) Gradient boosting models:
|
|
- regression tree (GBRT)
|
|
- 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
|