* Remove `learning_rates`.
It's been deprecated since we have callback.
* Set `before_iteration` of `reset_learning_rate` to False to preserve
the initial learning rate, and comply to the term "reset".
Closes#4709.
* Tests for various `tree_method`.
* Fix#3397: early_stop callback does not maximize metric of form NDCG@n-
Early stopping callback makes splits with '-' letter, which interferes
with metrics of form NDCG@n-. As a result, XGBoost tries to minimize
NDCG@n-, where it should be maximized instead.
Fix. Specify maxsplit=1.
* Python 2.x compatibility fix
verbose_eval docs claim it will log the last iteration (http://xgboost.readthedocs.io/en/latest/python/python_api.html#xgboost.train). this is also consistent w/the behavior from 0.4. not a huge deal but I found it handy to see the last iter's result b/c my period is usually large.
this doesn't address logging the last stage found by early_stopping (as noted in docs) as I'm not sure how to do that.
* Allow using learning_rates parameter when doing CV
- Create a new `callback_cv` method working when called from `xgb.cv()`
- Rename existing `callback` into `callback_train` and make it the default callback
- Get the logic out of the callbacks and place it into a common helper
* Add a learning_rates parameter to cv()
* lint
* remove caller explicit reference
* callback is aware of its calling context
* remove caller argument
* remove learning_rates param
* restore learning_rates for training, but deprecated
* lint
* lint line too long
* quick example for predefined callbacks
*Fix 1439
*Fix python_wrapper when eval set name contain '-' will cause early_stop maximize variable con't set to True propely
Change-Id: Ib0595afd4ae7b445a84c00a3a8faeccc506c6d13
