Update app.py

app.py

@@ -1,15 +1,25 @@
 import streamlit as st
 import pickle
 import numpy as np
+from tensorflow.keras.models import load_model
 
-# Load the saved model
+# Load the saved models
 with open('rf_model.pkl', 'rb') as file:
-    model = pickle.load(file)
+    rf_model = pickle.load(file)
+
+reloaded_model = load_model('deep_model.h5')
 
 # Define the function to make predictions
-def make_prediction(model, input_data):
-    prediction = model.predict(input_data)
-    return prediction
+def make_prediction(rf_model, nn_model, input_data):
+    # Predictions from RandomForestRegressor
+    rf_predictions = rf_model.predict(input_data)
+
+    # Predictions from Neural Network model
+    nn_predictions = nn_model.predict(input_data).flatten()
+
+    # Combine predictions
+    combined_predictions = (rf_predictions + nn_predictions) / 2  # Taking the average of predictions
+    return combined_predictions
 
 # Define the function to calculate GPA
 def calculate_gpa(total_score):
@@ -32,7 +42,7 @@ def main():
     # Add a title and description
     st.title("Exam Score Prediction")
     st.markdown(
-        "This app predicts exam scores based on input features such as level, course units, attendance, mid-semester score, and assignments."
+        "This app predicts exam scores based on input features such as level, course units, attendance, mid-semester score, and assignments using a combined model."
     )
 
     # Create input fields
@@ -49,17 +59,17 @@ def main():
     if st.button("Predict Exam Score"):
         # Add total_score to the input data
         input_data = np.array([[level, course_units, attendance, mid_semester, assignments]])
-        prediction = make_prediction(model, input_data)
+        prediction = make_prediction(rf_model, reloaded_model, input_data)
 
         # Calculate total score
         total_score = attendance + mid_semester + assignments + prediction[0]
 
         st.write(f"Predicted Exam Score: {prediction[0]:.2f}")
         st.write(f"Total Score: {total_score}")
-        
+
         # Calculate GPA
         gpa = calculate_gpa(total_score)
         st.write(f"Predicted GPA: {gpa}")
 
 if __name__ == '__main__':
-    main()
+    main()