Update app.py

app.py

@@ -1,5 +1,3 @@
-
-
 import gradio as gr
 import joblib
 import numpy as np
@@ -39,9 +37,9 @@ def predict_performance(Location, College_Fee,College, GPA, Year, Course_Interes
                  Visited_College_for_Inquiry_Only, Event, Attended_Any_Events,
                  Presenter, Visited_Parents]]
 
-    feature_names = ["Location", "College Fee","College", "GPA", "Year", "Course Interested",
-                    "Faculty", "Source", "Visited College for Inquiry Only", "Event",
-                    "Attended Any Events", "Presenter", "Visited Parents"]
+    feature_names = ["Location", "College Fee", "GPA", "Year", "Course Interested",
+                 "Faculty", "Source", "Visited College for Inquiry Only", "Event",
+                 "Attended Any Events", "College", "Presenter", "Visited Parents"]
     
     input_df = pd.DataFrame(input_data, columns=feature_names)
     
@@ -55,6 +53,9 @@ def predict_performance(Location, College_Fee,College, GPA, Year, Course_Interes
     print("\nDataFrame after encoding:")
     print(df)
     
+    # Ensure the DataFrame columns match the scaler's expected input
+    df = df.reindex(columns=scaler.feature_names_in_, fill_value=0)
+    
     scaled_input = scaler.transform(df)
     
     # Debug print 4: Show scaled input