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XGBoost: Difference between revisions
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'''[https://xgboost.readthedocs.io/en/latest/ XGBoost]''' ''is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable''. It is a popular package used for a wide variety of machine learning and datascience tasks, serving the role of a convenient, domain-agnostic black box classifier. XGBoost provides GPU accelerated learning for some problems, and Compute Canada provides a GPU enabled build. | '''[https://xgboost.readthedocs.io/en/latest/ XGBoost]''' ''is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable''. It is a popular package used for a wide variety of machine learning and datascience tasks, serving the role of a convenient, domain-agnostic black box classifier. XGBoost provides GPU accelerated learning for some problems, and Compute Canada provides a GPU enabled build. | ||
For detailed documentation on using the library, please consult the [https://xgboost.readthedocs.io/en/latest/get_started.html xgboost documentation]. There is a [https://xgboost.readthedocs.io/en/latest/gpu/index.html separate section for GPU-enabled training]. | |||
== Python Module Installation == | == Python Module Installation == | ||