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| import streamlit as st | |
| import pandas as pd | |
| import pickle | |
| st.image('images.jpeg') | |
| # Load the pickled model | |
| loaded_pickle_model = pickle.load(open("random_forest_model.pkl", "rb")) | |
| def predict_loan_approval(data): | |
| # Use the loaded model to make predictions | |
| prediction = loaded_pickle_model.predict(data) | |
| return prediction | |
| def main(): | |
| st.title("Loan Approval Prediction") | |
| # Input form for user to enter data | |
| st.header("Input Data") | |
| gender = st.selectbox("Gender", ["Male", "Female"]) | |
| married = st.selectbox("Married", ["Yes", "No"]) | |
| dependents = st.number_input("Dependents", min_value=0, max_value=10, value=0) | |
| education = st.selectbox("Education", ["Graduate", "Not Graduate"]) | |
| self_employed = st.selectbox("Self Employed", ["Yes", "No"]) | |
| applicant_income = st.number_input("Applicant Income", value=0) | |
| coapplicant_income = st.number_input("Coapplicant Income", value=0) | |
| loan_amount = st.number_input("Loan Amount", value=0) | |
| loan_amount_term = st.number_input("Loan Amount Term", value=0) | |
| credit_history = st.selectbox("Credit History", [0.0, 1.0]) | |
| property_area = st.selectbox("Property Area", ["Urban", "Semiurban", "Rural"]) | |
| # Mapping input values to numerical values | |
| gender_map = {'Male': 1, 'Female': 0} | |
| married_map = {'Yes': 1, 'No': 0} | |
| education_map = {'Graduate': 1, 'Not Graduate': 0} | |
| self_employed_map = {'Yes': 1, 'No': 0} | |
| property_area_map = {'Urban': 0, 'Semiurban': 1, 'Rural': 2} | |
| # Create a DataFrame from the input data | |
| new_data = pd.DataFrame({ | |
| 'Gender': [gender_map[gender]], | |
| 'Married': [married_map[married]], | |
| 'Dependents': [dependents], | |
| 'Education': [education_map[education]], | |
| 'Self_Employed': [self_employed_map[self_employed]], | |
| 'ApplicantIncome': [applicant_income], | |
| 'CoapplicantIncome': [coapplicant_income], | |
| 'LoanAmount': [loan_amount], | |
| 'Loan_Amount_Term': [loan_amount_term], | |
| 'Credit_History': [credit_history], | |
| 'Property_Area': [property_area_map[property_area]] | |
| }) | |
| # Button to predict loan approval | |
| if st.button("Predict Loan Approval"): | |
| prediction = predict_loan_approval(new_data) | |
| if prediction[0] == 1: | |
| st.success("Loan is Approved 👍") | |
| else: | |
| st.error("Loan is Rejected 👎") | |
| if __name__ == "__main__": | |
| main() |