Update main.py

main.py

@@ -46,8 +46,7 @@ async def predict(input:model_input):
     XGB= Pipeline([
     ("col_trans", full_pipeline),
     ("feature_selection", SelectKBest(score_func=f_classif, k='all')),
-    ("model", BaggingClassifier(base_estimator=XGBClassifier(random_state=42)))
-    ])
+    ("model", BaggingClassifier(base_estimator=XGBClassifier(random_state=42)))])
 
 #print(model_input)
     df = pd.DataFrame([input])