Update classification_model_monitor.py

classification_model_monitor.py

@@ -21,13 +21,11 @@ def filter_prediction_data(data: pd.DataFrame):
         if data is None:
             raise Exception("Input Prediction Data frame in None")   
 
-        filtered_prediction_data = data.loc[data['y_true_proba'] == 1].copy()
+        filtered_prediction_data = data.loc[(data['y_true_proba'] == 1) & (data['used_for_training'].astype("str").str.contains("_train")==False) & 
+                                                                          (data['used_for_training'].astype("str").str.contains("_excluded")==False) & 
+                                                                          (data['used_for_training'].astype("str").str.contains("_validation")==False) 
+                                           ].copy()
 
-        # filtered_prediction_data = data.loc[(data['y_true_proba'] == 1) & (data['used_for_training'].str.contains("_train")==False) & 
-        #                                                                   (data['used_for_training'].str.contains("_excluded")==False) & 
-        #                                                                   (data['used_for_training'].str.contains("_validation")==False), 
-        #                                     ['y_true', 'y_pred']].copy()
-            
         logging.info("Exiting filter_prediction_data()")
         return filtered_prediction_data
     except Exception as e: