45aef75cca
A new parameter `custom_metric` is added to `train` and `cv` to distinguish the behaviour from the old `feval`. And `feval` is deprecated. The new `custom_metric` receives transformed prediction when the built-in objective is used. This enables XGBoost to use cost functions from other libraries like scikit-learn directly without going through the definition of the link function. `eval_metric` and `early_stopping_rounds` in sklearn interface are moved from `fit` to `__init__` and is now saved as part of the scikit-learn model. The old ones in `fit` function are now deprecated. The new `eval_metric` in `__init__` has the same new behaviour as `custom_metric`. Added more detailed documents for the behaviour of custom objective and metric.
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XGBoost Python Package
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|PyPI version|
Installation
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From `PyPI <https://pypi.python.org/pypi/xgboost>`_
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For a stable version, install using ``pip``::
pip install xgboost
.. |PyPI version| image:: https://badge.fury.io/py/xgboost.svg
:target: http://badge.fury.io/py/xgboost
For building from source, see `build <https://xgboost.readthedocs.io/en/latest/build.html>`_.