Added SKLearn-like random forest Python API. (#4148)

* 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

python-package/xgboost/__init__.py

@@ -13,6 +13,7 @@ from .training import train, cv
 from . import rabit                   # noqa
 try:
     from .sklearn import XGBModel, XGBClassifier, XGBRegressor, XGBRanker
+    from .sklearn import XGBRFClassifier, XGBRFRegressor
     from .plotting import plot_importance, plot_tree, to_graphviz
 except ImportError:
     pass
@@ -24,4 +25,5 @@ with open(VERSION_FILE) as f:
 __all__ = ['DMatrix', 'Booster',
            'train', 'cv',
            'XGBModel', 'XGBClassifier', 'XGBRegressor', 'XGBRanker',
+           'XGBRFClassifier', 'XGBRFRegressor',
            'plot_importance', 'plot_tree', 'to_graphviz']