diff --git a/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_example.py b/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_example.py
index bd29bcb7d..1d7ac529d 100644
--- a/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_example.py
+++ b/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_example.py
@@ -12,7 +12,8 @@
             'eigen_basis',
             params={
                 'low_rank_approximation': False,
-                'rank_regularization': 'explained_dispersion'}).add_node('ar')}
+                'rank_regularization': 'explained_dispersion'}).add_node('ar')
+    }
     for assumption in initial_assumptions.keys():
         api_config = dict(problem='ts_forecasting',
                           metric='rmse',
@@ -24,4 +25,5 @@
         metric_names = ('r2', 'rmse', 'mae')
         model, labels, metrics = industrial_common_modelling_loop(
             api_config=api_config, dataset_name=dataset_name, finetune=finetune)
+        finetune = False
         print(f'{assumption} have metrics - {metrics}')
diff --git a/fedot_ind/core/operation/interfaces/industrial_preprocessing_strategy.py b/fedot_ind/core/operation/interfaces/industrial_preprocessing_strategy.py
index c2aeecfe0..66d5ca546 100644
--- a/fedot_ind/core/operation/interfaces/industrial_preprocessing_strategy.py
+++ b/fedot_ind/core/operation/interfaces/industrial_preprocessing_strategy.py
@@ -125,7 +125,7 @@ def _predict_for_ndim(self, predict_data, trained_operation: list):
 
             prediction = [
                 pred.predict for pred in prediction if not isinstance(
-                    pred, np.array)]
+                    pred, np.ndarray)]
 
         if not isinstance(prediction[0], OutputData):
             prediction = NumpyConverter(