xgboost v0.4-2
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Extreme Gradient Boosting
Extreme Gradient Boosting, which is an
efficient implementation of gradient boosting framework.
This package is its R interface. The package includes efficient
linear model solver and tree learning algorithms. The package can automatically
do parallel computation on a single machine which could be more than 10 times faster
than existing gradient boosting packages. 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 | |
| xgb.DMatrix | Contruct xgb.DMatrix object | |
| setinfo | Set information of an xgb.DMatrix object | |
| xgb.DMatrix.save | Save xgb.DMatrix object to binary file | |
| slice | Get a new DMatrix containing the specified rows of orginal xgb.DMatrix object | |
| xgb.importance | Show importance of features in a model | |
| xgb.save.raw | Save xgboost model to R's raw vector, user can call xgb.load to load the model back from raw vector | |
| xgb.dump | Save xgboost model to text file | |
| xgb.model.dt.tree | Convert tree model dump to data.table | |
| nrow,xgb.DMatrix-method | Number of xgb.DMatrix rows | |
| predict,xgb.Booster-method | Predict method for eXtreme Gradient Boosting model | |
| xgb.cv | Cross Validation | |
| agaricus.test | Test part from Mushroom Data Set | |
| xgb.plot.importance | Plot feature importance bar graph | |
| xgb.save | Save xgboost model to binary file | |
| xgboost | eXtreme Gradient Boosting (Tree) library | |
| xgb.load | Load xgboost model from binary file | |
| getinfo | Get information of an xgb.DMatrix object | |
| xgb.train | eXtreme Gradient Boosting Training | |
| xgb.plot.tree | Plot a boosted tree model | |
| predict,xgb.Booster.handle-method | Predict method for eXtreme Gradient Boosting model handle | |
| agaricus.train | Training part from Mushroom Data Set | |
| No Results! | ||
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Details
| Type | Package |
| Date | 2015-08-01 |
| License | Apache License (== 2.0) | file LICENSE |
| URL | https://github.com/dmlc/xgboost |
| BugReports | https://github.com/dmlc/xgboost/issues |
| VignetteBuilder | knitr |
| NeedsCompilation | yes |
| Packaged | 2015-08-01 18:21:31 UTC; ubuntu |
| Repository | CRAN |
| Date/Publication | 2015-08-02 08:23:27 |
| depends | base (>= 2.10) , R (>= 2.10) |
| suggests | Ckmeans , Ckmeans.1d.dp (>= 3.3.1) , DiagrammeR (>= 0.6) , ggplot2 (>= 1.0.0) , knitr , vcd (>= 1.3) |
| imports | data , data.table (>= 1.9.4) , magrittr (>= 1.5) , Matrix (>= 1.1-0) , methods , stringr (>= 0.6.2) |
| Contributors | Tianqi Chen, Tong He, Michael Benesty |
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