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| import streamlit as st | |
| import joblib | |
| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| # Load Model | |
| model=joblib.load('Rf_model.joblib') | |
| encoder=joblib.load('encoder_d.joblib') | |
| # Streamlit app | |
| def main(): | |
| st.title("Insurance Cost Prediction App") | |
| # User inputs | |
| age = st.number_input("Age", min_value=18, max_value=100, value=30) | |
| sex = st.selectbox("Sex", encoder["sex"].classes_) | |
| sex=encoder['sex'].transform([sex])[0] | |
| bmi = st.number_input("BMI", min_value=10.0, max_value=50.0, value=25.0) | |
| children = st.number_input("Children", min_value=0, max_value=10, value=0) | |
| smoker = st.selectbox("Smoker", encoder['smoker'].classes_) | |
| smoker=encoder['smoker'].transform([smoker])[0] | |
| region = st.selectbox("Region", encoder['region'].classes_) | |
| region=encoder['region'].transform([region])[0] | |
| # Predict button | |
| if st.button("Predict Insurance Cost"): | |
| values=[age,sex,bmi,children, smoker,region] | |
| predict = round(model.predict([values])[0],2) | |
| st.success(f"Estimated Insurance Cost: ${predict}") | |
| if __name__ == "__main__": | |
| main() |