diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index c05900bad..766eb981f 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -1,6 +1,5 @@
 import copy
 import logging
-import re
 import shutil
 from datetime import datetime, timezone
 from math import cos, sin
@@ -882,9 +881,6 @@ class FreqaiDataKitchen:
         """
         column_names = dataframe.columns
         features = [c for c in column_names if "%" in c]
-        pca_features = [c for c in column_names if re.search(r"^PC\d+$", c)]
-        if not features and pca_features:
-            features = pca_features
 
         if not features:
             raise OperationalException("Could not find any features!")
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index bf625b2a7..5cc6d3f69 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -275,7 +275,8 @@ class IFreqaiModel(ABC):
 
             if dk.check_if_backtest_prediction_exists():
                 self.dd.load_metadata(dk)
-                self.check_if_feature_list_matches_strategy(dataframe_train, dk)
+                dk.find_features(dataframe_train)
+                self.check_if_feature_list_matches_strategy(dk)
                 append_df = dk.get_backtesting_prediction()
                 dk.append_predictions(append_df)
             else:
@@ -296,7 +297,6 @@ class IFreqaiModel(ABC):
                 else:
                     self.model = self.dd.load_data(pair, dk)
 
-                # self.check_if_feature_list_matches_strategy(dataframe_train, dk)
                 pred_df, do_preds = self.predict(dataframe_backtest, dk)
                 append_df = dk.get_predictions_to_append(pred_df, do_preds)
                 dk.append_predictions(append_df)
@@ -420,7 +420,7 @@ class IFreqaiModel(ABC):
         return
 
     def check_if_feature_list_matches_strategy(
-        self, dataframe: DataFrame, dk: FreqaiDataKitchen
+        self, dk: FreqaiDataKitchen
     ) -> None:
         """
         Ensure user is passing the proper feature set if they are reusing an `identifier` pointing
@@ -429,15 +429,12 @@ class IFreqaiModel(ABC):
         :param dk: FreqaiDataKitchen = non-persistent data container/analyzer for
                    current coin/bot loop
         """
-        dk.find_features(dataframe)
+
         if "training_features_list_raw" in dk.data:
             feature_list = dk.data["training_features_list_raw"]
         else:
             feature_list = dk.data['training_features_list']
 
-        if self.ft_params.get('principal_component_analysis', False):
-            feature_list = dk.data['training_features_list']
-
         if dk.training_features_list != feature_list:
             raise OperationalException(
                 "Trying to access pretrained model with `identifier` "
@@ -510,7 +507,7 @@ class IFreqaiModel(ABC):
             dk.use_DBSCAN_to_remove_outliers(predict=True)
 
         # ensure user is feeding the correct indicators to the model
-        self.check_if_feature_list_matches_strategy(dk.data_dictionary['prediction_features'], dk)
+        self.check_if_feature_list_matches_strategy(dk)
 
     def model_exists(self, dk: FreqaiDataKitchen) -> bool:
         """