xgboost v0.6-3
Monthly downloads
Extreme Gradient Boosting
Extreme Gradient Boosting, which is an efficient implementation
of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
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 | |
| dim.xgb.DMatrix | Dimensions of xgb.DMatrix | |
| cb.evaluation.log | Callback closure for logging the evaluation history | |
| cb.cv.predict | Callback closure for returning cross-validation based predictions. | |
| cb.save.model | Callback closure for saving a model file. | |
| cb.early.stop | Callback closure to activate the early stopping. | |
| agaricus.train | Training part from Mushroom Data Set | |
| cb.reset.parameters | Callback closure for restetting the booster's parameters at each iteration. | |
| agaricus.test | Test part from Mushroom Data Set | |
| slice | Get a new DMatrix containing the specified rows of orginal xgb.DMatrix object | |
| setinfo | Set information of an xgb.DMatrix object | |
| predict.xgb.Booster | Predict method for eXtreme Gradient Boosting model | |
| getinfo | Get information of an xgb.DMatrix object | |
| dimnames.xgb.DMatrix | Handling of column names of xgb.DMatrix | |
| xgb.attr | Accessors for serializable attributes of a model. | |
| print.xgb.cv.synchronous | Print xgb.cv result | |
| xgb.create.features | Create new features from a previously learned model | |
| print.xgb.DMatrix | Print xgb.DMatrix | |
| xgb.ggplot.deepness | Plot model trees deepness | |
| xgb.ggplot.importance | Plot feature importance as a bar graph | |
| print.xgb.Booster | Print xgb.Booster | |
| xgb.DMatrix | Contruct xgb.DMatrix object | |
| xgb.cv | Cross Validation | |
| xgb.save | Save xgboost model to binary file | |
| 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.load | Load xgboost model from binary file | |
| xgboost-deprecated | Deprecation notices. | |
| xgb.train | eXtreme Gradient Boosting Training | |
| xgb.DMatrix.save | Save xgb.DMatrix object to binary file | |
| xgb.dump | Save xgboost model to text file | |
| xgb.plot.tree | Plot a boosted tree model | |
| xgb.plot.multi.trees | Project all trees on one tree and plot it | |
| cb.print.evaluation | Callback closure for printing the result of evaluation | |
| callbacks | Callback closures for booster training. | |
| xgb.model.dt.tree | Parse a boosted tree model text dump | |
| xgb.parameters<- | Accessors for model parameters. | |
| No Results! | ||
Last month downloads
Details
| Type | Package |
| Date | 2016-12-28 |
| License | Apache License (== 2.0) | file LICENSE |
| URL | https://github.com/dmlc/xgboost |
| BugReports | https://github.com/dmlc/xgboost/issues |
| VignetteBuilder | knitr |
| RoxygenNote | 5.0.1 |
| NeedsCompilation | yes |
| Packaged | 2016-12-31 19:14:32 UTC; hetong007 |
| Repository | CRAN |
| Date/Publication | 2016-12-31 22:01:56 |
| suggests | Ckmeans.1d.dp (>= 3.3.1) , DiagrammeR (>= 0.8.1) , ggplot2 (>= 1.0.1) , igraph (>= 1.0.1) , knitr , rmarkdown , testthat , vcd (>= 1.3) |
| imports | data.table (>= 1.9.6) , magrittr (>= 1.5) , Matrix (>= 1.1-0) , methods , stringi (>= 0.5.2) |
| depends | R (>= 3.3.0) |
| Contributors | Tianqi Chen, Yuan Tang, Tong He, Michael Benesty, Vadim Khotilovich |
Include our badge in your README
[](http://www.rdocumentation.org/packages/xgboost)