diff --git a/freqtrade/freqai/RL/BaseReinforcementLearningModel.py b/freqtrade/freqai/RL/BaseReinforcementLearningModel.py
index b59c47ad2..81cacc055 100644
--- a/freqtrade/freqai/RL/BaseReinforcementLearningModel.py
+++ b/freqtrade/freqai/RL/BaseReinforcementLearningModel.py
@@ -250,17 +250,13 @@ class BaseReinforcementLearningModel(IFreqaiModel):
 
         dk.data_dictionary["prediction_features"] = self.drop_ohlc_from_df(filtered_dataframe, dk)
 
-        dk.data_dictionary["prediction_features"], outliers, _ = dk.feature_pipeline.transform(
+        dk.data_dictionary["prediction_features"], _, _ = dk.feature_pipeline.transform(
             dk.data_dictionary["prediction_features"], outlier_check=True)
 
         pred_df = self.rl_model_predict(
             dk.data_dictionary["prediction_features"], dk, self.model)
         pred_df.fillna(0, inplace=True)
 
-        if self.freqai_info.get("DI_threshold", 0) > 0:
-            dk.DI_values = dk.feature_pipeline["di"].di_values
-        dk.do_predict = outliers.to_numpy()
-
         return (pred_df, dk.do_predict)
 
     def rl_model_predict(self, dataframe: DataFrame,
diff --git a/freqtrade/freqai/base_models/BasePyTorchRegressor.py b/freqtrade/freqai/base_models/BasePyTorchRegressor.py
index ec4d6b80c..b77fec31a 100644
--- a/freqtrade/freqai/base_models/BasePyTorchRegressor.py
+++ b/freqtrade/freqai/base_models/BasePyTorchRegressor.py
@@ -52,7 +52,7 @@ class BasePyTorchRegressor(BasePyTorchModel):
         pred_df = DataFrame(y.detach().tolist(), columns=[dk.label_list[0]])
         pred_df, _, _ = dk.label_pipeline.inverse_transform(pred_df)
 
-        if self.freqai_info.get("DI_threshold", 0) > 0:
+        if dk.feature_pipeline["di"]:
             dk.DI_values = dk.feature_pipeline["di"].di_values
         else:
             dk.DI_values = np.zeros(len(outliers.index))
diff --git a/freqtrade/freqai/base_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py
index f1e33bff8..3cce978b5 100644
--- a/freqtrade/freqai/base_models/BaseRegressionModel.py
+++ b/freqtrade/freqai/base_models/BaseRegressionModel.py
@@ -111,7 +111,7 @@ class BaseRegressionModel(IFreqaiModel):
         pred_df = DataFrame(predictions, columns=dk.label_list)
 
         pred_df, _, _ = dk.label_pipeline.inverse_transform(pred_df)
-        if self.freqai_info.get("DI_threshold", 0) > 0:
+        if dk.feature_pipeline["di"]:
             dk.DI_values = dk.feature_pipeline["di"].di_values
         else:
             dk.DI_values = np.zeros(len(outliers.index))