Clarification for learning_rates

python-package/xgboost/training.py

@@ -50,7 +50,9 @@ def train(params, dtrain, num_boost_round=10, evals=(), obj=None, feval=None,
         If `verbose_eval` then the evaluation metric on the validation set, if
         given, is printed at each boosting stage.
     learning_rates: list or function
-        Learning rate for each boosting round (yields learning rate decay).
+        List of learning rate for each boosting round 
+        or a customized function that calculates eta in terms of 
+        current number of round and the total number of boosting round (e.g. yields learning rate decay)
         - list l: eta = l[boosting round]
         - function f: eta = f(boosting round, num_boost_round)
     xgb_model : file name of stored xgb model or 'Booster' instance