XGBoost R Feature Walkthrough
====
* [Basic walkthrough of wrappers](basic_walkthrough.R)
* [Train a xgboost model from caret library](caret_wrapper.R)
* [Cutomize loss function, and evaluation metric](custom_objective.R)
* [Boosting from existing prediction](boost_from_prediction.R)
* [Predicting using first n trees](predict_first_ntree.R)
* [Generalized Linear Model](generalized_linear_model.R)
* [Cross validation](cross_validation.R)
* [Create a sparse matrix from a dense one](create_sparse_matrix.R)
* [Use GPU-accelerated tree building algorithms](gpu_accelerated.R)

Benchmarks
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* [Starter script for Kaggle Higgs Boson](../../demo/kaggle-higgs)
 
Notes
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* Contribution of examples, benchmarks is more than welcomed!
* If you like to share how you use xgboost to solve your problem, send a pull request:)
