Update app.py

app.py

@@ -2,8 +2,7 @@ import pickle as pkl
 import streamlit as st
 from sklearn.linear_model import LinearRegression
 
-#Step 2: Open the saved file with read-binary mode
-lr_pickle = pkl.load(open('linear_saved_model', 'rb'))
+
 
 # FUNCTION
 def user_report():
@@ -32,11 +31,13 @@ user_data = user_report()
 st.subheader('Housing Data')
 st.write(user_data)
 
-
+lr = LinearRegression()
+#Open the saved file with read-binary mode
+lr_pickle = pkl.load(open('linear_saved_model', 'rb'))
 
 
 # MODEL
-user_result = lr_pickle.predict(user_data)
+user_result = lr.predict(user_data)