Gxnc/RealEstatePricePred

1 2import streamlit as st3import joblib4import numpy as np5 6# Load model7model = joblib.load("linear_regression_model.pkl")8 9# Title10st.title("🏡 Real Estate Price Predictor")11 12# Inputs13mrt = st.number_input("Distance to nearest MRT station (m)", min_value=0, value=500)14stores = st.number_input("Number of convenience stores", min_value=0, step=1, value=5)15latitude = st.number_input("Latitude", min_value=24.9, max_value=25.1, value=25.0, step=0.0001)16 17# Prediction18if st.button("Predict"):19    features = np.array([[mrt, stores, latitude]])20    prediction = model.predict(features)[0]21    st.success(f"💰 Predicted Price per Unit Area: {prediction:.2f}")22