eXtreme Gradient Boosting
This package is a R wrapper of xgboost, which is short for eXtreme Gradient Boosting.
It is an efficient and scalable implementation of gradient boosting framework.
The package includes efficient linear model solver and tree learning algorithm.
The package can automatically do parallel computation with OpenMP, and it can be
more than 10 times faster than existing gradient boosting packages such as gbm.
It supports various objective functions, including regression, classification and ranking.
The package is made to be extensible, so that user are also allowed to define there own objectives easily.
Functions in xgboost
|xgb.load||Load xgboost model from binary file|
|xgb.DMatrix.save||Save xgb.DMatrix object to binary file|
|xgb.dump||Save xgboost model to text file|
|xgboost||eXtreme Gradient Boosting (Tree) library|
|slice||Get a new DMatrix containing the specified rows of orginal xgb.DMatrix object|
|xgb.DMatrix||Contruct xgb.DMatrix object|
|xgb.save||Save xgboost model to binary file|
|predict,xgb.Booster-method||Predict method for eXtreme Gradient Boosting model|
|xgb.train||eXtreme Gradient Boosting Training|
|getinfo||Get information of an xgb.DMatrix object|
Last month downloads
|License||Apache License (== 2.0) | file LICENSE|
|Packaged||2014-09-01 16:17:30 UTC; hetong|
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