Fix model feature names

app.py

@@ -15,11 +15,11 @@ model_dir = model.download()
 model = joblib.load(model_dir + "/wine_class_model.pkl")
 print("Model downloaded")
 
-def wine_quality_class(wine_type_name, fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, ph, sulphates, alcohol):
+def wine_quality_class(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, ph, sulphates, alcohol, wine_type_name):
     print("Calling function")
-    type_wine = 1.0 if wine_type_name == "white" else 0.0
-    df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, ph, sulphates, alcohol, type_wine]], 
-                      columns=['fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','density','ph','sulphates','alcohol','type_wine'])
+    type_white = 1.0 if wine_type_name == "white" else 0.0
+    df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, ph, sulphates, alcohol, type_white]], 
+                      columns=['fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','density','ph','sulphates','alcohol','type_white'])
     print("Predicting")
     print(df)
     # 'res' is a list of predictions returned as the label.