Move skl eval_metric and early_stopping rounds to model params. (#6751)

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.

tests/python/test_early_stopping.py

@@ -7,7 +7,6 @@ rng = np.random.RandomState(1994)
 
 
 class TestEarlyStopping:
-
     @pytest.mark.skipif(**tm.no_sklearn())
     def test_early_stopping_nonparallel(self):
         from sklearn.datasets import load_digits