# xgboost v0.3-2

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by Tong He

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 No Results!