* Add back xgboost.rabit for backwards compatibility
* fix my errors
* Fix lint
* Use FutureWarning
Co-authored-by: Hyunsu Philip Cho <chohyu01@cs.washington.edu>
* Add management functions for global configuration: XGBSetGlobalConfig(), XGBGetGlobalConfig().
* Add Python interface: set_config(), get_config(), and config_context().
* Add unit tests for Python
* Add R interface: xgb.set.config(), xgb.get.config()
* Add unit tests for R
Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
* Remove f-string, since it's not supported by Python 3.5 (#5330)
* Remove f-string, since it's not supported by Python 3.5
* Add Python 3.5 to CI, to ensure compatibility
* Remove duplicated matplotlib
* Show deprecation notice for Python 3.5
* Fix lint
* Fix lint
* Fix a unit test that mistook MINOR ver for PATCH ver
* Enforce only major version in JSON model schema
* Bump version to 1.1.0-SNAPSHOT
* Added SKLearn-like random forest Python API.
- added XGBRFClassifier and XGBRFRegressor classes to SKL-like xgboost API
- also added n_gpus and gpu_id parameters to SKL classes
- added documentation describing how to use xgboost for random forests,
as well as existing caveats
* Add XGBRanker to Python API doc
* Show inherited members of XGBRegressor in API doc, since XGBRegressor uses default methods from XGBModel
* Add table of contents to Python API doc
* Skip JVM doc download if not available
* Show inherited members for XGBRegressor and XGBRanker
* Expose XGBRanker to Python XGBoost module directory
* Add docstring to XGBRegressor.predict() and XGBRanker.predict()
* Fix rendering errors in Python docstrings
* Fix lint
Currently `pip install xgboost` will raise traceback like this
```
Traceback (most recent call last):
File "<string>", line 20, in <module>
File "/tmp/pip-build-IAdqYE/xgboost/setup.py", line 20, in <module>
import xgboost
File "./xgboost/__init__.py", line 8, in <module>
from .core import DMatrix, Booster
File "./xgboost/core.py", line 12, in <module>
import numpy as np
ImportError: No module named numpy
```
We should avoid importing numpy in setup.py and let pip install numpy and scipy automatically.
That's what `install_requires` for.
