92ae3abc97
* Disallow importing non-dask estimators from xgboost.dask This is mostly a style change, but also avoids a user error (that I have committed on a few occasions). Since `XGBRegressor` and `XGBClassifier` are imported as parent classes for the `dask` estimators, without defining an `__all__`, autocomplete (or muscle) memory will produce the following with little prompting: ``` from xgboost.dask import XGBClassifier ``` There's nothing inherently wrong with that, but given that `XGBClassifier` is not `dask` enabled, it can lead to confusing behavior until you figure out you should've typed ``` from xgboost.dask import DaskXGBClassifier ``` Another option is to alias import the existing non-dask estimators. * Remove base/iter class, add train predict funcs
eXtreme Gradient Boosting
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XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples.
License
© Contributors, 2019. Licensed under an Apache-2 license.
Contribute to XGBoost
XGBoost has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone. Checkout the Community Page.
Reference
- Tianqi Chen and Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. In 22nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2016
- XGBoost originates from research project at University of Washington.
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