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| import streamlit as st | |
| import pandas as pd | |
| import joblib | |
| from huggingface_hub import hf_hub_download | |
| st.set_page_config(page_title="Tourism Predictor", page_icon="βοΈ") | |
| def load_model(): | |
| model_path = hf_hub_download("Supreeth15/tourism-model", "best_model.pkl") | |
| return joblib.load(model_path) | |
| st.title("π Tourism Package Predictor") | |
| st.write("Predict Wellness Tourism Package purchase") | |
| model = load_model() | |
| st.success("β Model loaded: Bagging") | |
| # Input form | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| age = st.number_input("Age", 18, 100, 30) | |
| income = st.number_input("Monthly Income", 0, 200000, 30000) | |
| with col2: | |
| trips = st.number_input("Number of Trips", 0, 20, 2) | |
| passport = st.selectbox("Passport", [0, 1]) | |
| if st.button("Predict"): | |
| st.info("Demo prediction interface") | |
| st.write("Model: Bagging") | |
| st.write("ROC-AUC: 0.9584") | |