Update app.py

app.py

@@ -11,12 +11,13 @@ KNN_Regressor = load('knn_lab4.joblib')
 
 def predictPrice(input1, input2, input3, input4, input5, input6, input7, input8):
   features = [input1, input2, input3, input4, input5, input6, input7, input8]
-  scaler.fit(features)
-  features_array = np.array(features).reshape(1, -1)
+  normalized_features = scaler.transform(features)
+  features_array = np.array(normalized_features).reshape(1, -1)
   prediction = KNN_Regressor.predict(features_array)
   return prediction
 
 
+
 ## Buidling inputs and outputs:
 
 input1 = gr.Slider(-124.35, -114.31, step=5, label = "Longitude")