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* Speed: XGBoost is very fast
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- IN [demo/higgs/speedtest.py](demo/kaggle-higgs/speedtest.py), kaggle higgs data it is faster(on our machine 20 times faster using 4 threads) than sklearn.ensemble.GradientBoostingClassifier
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* Layout of gradient boosting algorithm to support user defined objective
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* Python interface, works with numpy and scipy.sparse matrix
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Languages
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=====
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* Standalone console version is supported, you can call xgboost from command line
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* [XGBoost Python](wrapper)
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* [XGBoost R](R-package)
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* [XGBoost Julia](https://github.com/antinucleon/XGBoost.jl)
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Build
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=====
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