change parameter order of train() function to be consistant with other gbdt libraries
@@ -1948,20 +1948,30 @@ class CatBoostRegressor(CatBoost):
return np.sqrt(np.mean(error))
-def train(pool=None, params=None, dtrain=None, logging_level=None, verbose=None, iterations=None, num_boost_round=None, evals=None, eval_set=None, plot=None):
+def train(params=None, pool=None, iterations=None, evals=None, verbose=None, dtrain=None, logging_level=None, num_boost_round=None, eval_set=None, plot=None):
"""
Train CatBoost model.
Parameters
----------
- pool : Pool or tuple (X, y)
- Data to train on.
-
params : dict
Parameters for CatBoost.
If None, all params are set to their defaults.
If dict, overriding parameters present in the dict.
+ pool : Pool or tuple (X, y)
+ Data to train on.
+
+ iterations : int
+ Number of boosting iterations. Can be set in params dict.
+
+ evals : Pool or tuple (X, y)
+ Synonym for evals. Only one of these parameters should be set.
+
+ verbose : bool
+ If set to True, then logging_level is set to Verbose, otherwise
+ logging_level is set to Silent.
+
dtrain : Pool or tuple (X, y)
Synonym for pool parameter. Only one of these parameters should be set.
@@ -1972,22 +1982,12 @@ def train(pool=None, params=None, dtrain=None, logging_level=None, verbose=None,
- 'Info'
- 'Debug'
- verbose : bool
- If set to True, then logging_level is set to Verbose, otherwise
- logging_level is set to Silent.
-
- iterations : int
- Number of boosting iterations. Can be set in params dict.
-
num_boost_round : int
Synonym for iterations. Only one of these parameters should be set.
eval_set : Pool or tuple (X, y)
Dataset for evaluation.
- evals : Pool or tuple (X, y)
- Synonym for evals. Only one of these parameters should be set.
-
plot : bool, optional (default=False)
If True, drow train and eval error in Jupyter notebook
