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README.md
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README.md
@ -8,9 +8,22 @@ Turorial and Documentation: https://github.com/tqchen/xgboost/wiki
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Questions and Issues: [https://github.com/tqchen/xgboost/issues](https://github.com/tqchen/xgboost/issues?q=is%3Aissue+label%3Aquestion)
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Features
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=======
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* Sparse feature format:
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- Sparse feature format allows easy handling of missing values, and improve computation efficiency.
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* Push the limit on single machine:
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- Efficient implementation that optimizes memory and computation.
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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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xgboost-unity
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=======
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experimental branch(not usable yet): refactor xgboost, cleaner code, more flexibility
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* experimental branch(not usable yet): refactor xgboost, cleaner code, more flexibility
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* This version of xgboost is not backward compatible with 0.2*, due to huge change in code structure
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- This means the model and buffer file of previous version can not be loaded in xgboost-unity
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Build
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======
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