xgboost

History

This PR rewrites the approx tree method to use codebase from hist for better performance and code sharing.

The rewrite has many benefits:
- Support for both `max_leaves` and `max_depth`.
- Support for `grow_policy`.
- Support for mono constraint.
- Support for feature weights.
- Support for easier bin configuration (`max_bin`).
- Support for categorical data.
- Faster performance for most of the datasets. (many times faster)
- Support for prediction cache.
- Significantly better performance for external memory.
- Unites the code base between approx and hist.

2022-01-10 21:15:05 +08:00

xgboost

Rewrite approx (#7214 )

2022-01-10 21:15:05 +08:00

.gitignore

python package refactor into python-package

2015-07-30 22:04:45 -07:00

.pylintrc

Improved sklearn compatibility (#5255 )

2020-02-03 13:30:45 +08:00

MANIFEST.in

[python-package] remove unnecessary files to reduce sdist size (fixes #6560 ) (#6565 )

2021-01-02 15:56:39 +08:00

README.rst

Fix Python demo and doc. (#4545 )

2019-06-11 08:58:41 +08:00

setup.cfg

Typehint for Sklearn. (#6799 )

2021-04-14 06:55:21 +08:00

setup.py

Update setup.py. (#7360 )

2021-10-28 14:58:31 +08:00

README.rst

======================
XGBoost Python Package
======================

|PyPI version|

Installation
============

From `PyPI <https://pypi.python.org/pypi/xgboost>`_
---------------------------------------------------

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>`_.