Update app.py

app.py

@@ -26,10 +26,11 @@ df["Diabetes"] = df["Outcome"].apply(lambda x: "Diabetic" if x == 1 else "Not_Di
 df["BMI"] = df["BMI"].apply(lambda x: df.BMI.mean() if x > 40 else x)
 
 from pycaret.classification import *
-
-# Diab = setup(data = df,target = 'Outcome',normalize=True, session_id=1,fix_imbalance = True)
-Diab = setup(data=df,target="Diabetes",normalize=True,session_id=1,fix_imbalance=True,numeric_features=["Pregnancies"],log_experiment=True,experiment_name="diabetes",ignore_features=["Outcome"]
-)
+print("1")
+Diab = setup(data = df,target = 'Diabetes',normalize=True, session_id=1,fix_imbalance = True)
+print("2")
+#Diab = setup(data=df,target="Diabetes",normalize=True,session_id=1,fix_imbalance=True,numeric_features=["Pregnancies"],log_experiment=True,experiment_name="diabetes",ignore_features=["Outcome"]
+#)
 
 best = compare_models(n_select=15)
 compare_model_results = pull()