xgboost v0.3-2


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by Tong He

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 algorithms. 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 users are also allowed to define their own objectives easily.

Functions in xgboost

Name Description
predict,xgb.Booster-method Predict method for eXtreme Gradient Boosting model
xgb.train eXtreme Gradient Boosting Training
xgb.cv Cross Validation
xgb.DMatrix.save Save xgb.DMatrix object to binary file
xgb.load Load xgboost model from binary file
xgb.save Save xgboost model to binary file
xgboost eXtreme Gradient Boosting (Tree) library
slice Get a new DMatrix containing the specified rows of orginal xgb.DMatrix object
agaricus.train Training part from Mushroom Data Set
getinfo Get information of an xgb.DMatrix object
xgb.DMatrix Contruct xgb.DMatrix object
xgb.dump Save xgboost model to text file
agaricus.test Test part from Mushroom Data Set
setinfo Set information of an xgb.DMatrix object
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Type Package
Date 2014-08-23
License Apache License (== 2.0) | file LICENSE
URL https://github.com/tqchen/xgboost
BugReports https://github.com/tqchen/xgboost/issues
Packaged 2014-09-07 17:42:19 UTC; hetong
NeedsCompilation yes
Repository CRAN
Date/Publication 2014-09-07 21:54:44

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