xgboost v0.3-2
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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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Details
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 |
depends | base (>= 2.10) , R (>= 2.10) |
imports | Matrix (>= 1.1-0) , methods |
Contributors | Tianqi Chen, Tong He |
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