Open Sandy4321 opened 6 years ago
Same here. Probably related to https://github.com/catboost/catboost/blob/master/RELEASE.md#breaking-changes-2
Had it working with pip install catboost==0.1.1.2
Had it working with
pip install catboost==0.1.1.2
How can we solve this problem if we use catboost==0.11.1?
Had it working with
pip install catboost==0.1.1.2
How can we solve this problem if we use catboost==0.11.1?
I got it! I've deleted the 'calc_feature_importance=True' in utils_models.py,and then it works!
Hey there! It appears that this repository is no longer being actively maintained. However, I still think it's a great idea, so I've started working on my own version of it, which you can find here. It's worth pointing out that I've dropped Python 2.7 support, so you'll have to upgrade if you haven't already.
P.S. @xingyuezhiji is correct, that fixes the issue.
Had it working with
pip install catboost==0.1.1.2
How can we solve this problem if we use catboost==0.11.1?
I got it! I've deleted the 'calc_feature_importance=True' in utils_models.py,and then it works!
Can you please tell me how did you do that?
error for test case
code from auto_ml import Predictor from auto_ml.utils import get_boston_dataset
df_train, df_test = get_boston_dataset()
column_descriptions = { 'MEDV': 'output', 'CHAS': 'categorical' }
ml_predictor = Predictor(type_of_estimator='regressor', column_descriptions=column_descriptions)
ml_predictor.train(df_train)
ml_predictor.score(df_test, df_test.MEDV) q=1
error message
File "E:\my_code\s_auto_ml_test_sep20.py", line 13, in
ml_predictor.train(df_train)
File "C:\Users\sndr\Anaconda3\Lib\site-packages\auto_ml\predictor.py", line 652, in train
X_df = self.fit_transformation_pipeline(X_df, y, estimator_names)
File "C:\Users\sndr\Anaconda3\Lib\site-packages\auto_ml\predictor.py", line 899, in fit_transformation_pipeline
ppl = self._construct_pipeline(model_name=model_names[0], keep_cat_features=self.keep_cat_features)
File "C:\Users\sndr\Anaconda3\Lib\site-packages\auto_ml\predictor.py", line 204, in _construct_pipeline
final_model = utils_models.get_model_from_name(model_name, training_params=params)
File "C:\Users\sndr\Anaconda3\Lib\site-packages\auto_ml\utils_models.py", line 176, in get_model_from_name
model_map['CatBoostRegressor'] = CatBoostRegressor(calc_feature_importance=True)
builtins.TypeError: init() got an unexpected keyword argument 'calc_feature_importance'