| import pandas as pd |
| import joblib |
| import streamlit as st |
| import warnings |
| warnings.filterwarnings("ignore") |
|
|
| st.set_page_config(page_title="Student Success Prediction", page_icon="💡") |
|
|
| model = joblib.load("lo_model.pkl") |
| col = joblib.load("columns.pkl") |
| scaler = joblib.load("Scaler.pkl") |
|
|
| st.title("Student Success Prediction APP 🏆🎖️") |
| sh = st.number_input("Study Hours",1,20,5) |
| at = st.slider("Attendance",0.0,100.0,50.0) |
| ps = st.slider("Past Score",0.0,100.0,50.0) |
| s = st.number_input("Sleep Hours",4,15,8) |
| print(model) |
| if st.button("Predict"): |
| try: |
| user_input_df = pd.DataFrame([{ |
| "StudyHours": sh, |
| "Attendance": at, |
| "PastScore": ps, |
| "SleepHours": s |
| }]) |
| user_input_df = user_input_df[col] |
| user_input_scaled = scaler.transform(user_input_df) |
| prediction = model.predict(user_input_scaled) |
| if prediction[0] == 1: |
| st.success("🎉 Result: Pass 😃") |
| else: |
| st.error("❌ Result: Fail 😥") |
| |
| except Exception as e: |
| st.error(f"Error: {e}") |
|
|
|
|
