Spaces:
Sleeping
Sleeping
| # Import Essential Library | |
| import streamlit as st | |
| import pandas as pd | |
| import pickle | |
| # Load Model | |
| with open('model.pkl', 'rb') as file: | |
| model = pickle.load(file) | |
| list_cat_cols = ['education_level', 'pay_sep05', 'pay_aug05', 'pay_jul05', 'pay_jun05', 'pay_may05', 'pay_apr05'] | |
| list_num_cols = ['limit_balance', 'pay_amt_sep05', 'pay_amt_aug05', 'pay_amt_jul05', 'pay_amt_jun05', 'pay_amt_may05', 'pay_amt_apr05'] | |
| # Function to run model predictor | |
| def run(): | |
| # Set Title | |
| st.title('Insurance Lead Prediction Model') | |
| # Sub Title | |
| st.subheader('Model Predict Section') | |
| st.markdown('---') | |
| # Insert Image | |
| st.image('https://www.startinsland.de/site/assets/files/4129/tk-logo_koop_official_health_partner_pos.800x0.png') | |
| # Creating Form for Data Inference | |
| st.markdown('## Input Data') | |
| with st.form('my_form'): | |
| Holding_Policy_Duration = st.slider('Holding Policy Duration', min_value=1, max_value=14, value=2, step=1) | |
| Holding_Policy_Type = st.selectbox('Holding Policy Type', (1, 2, 3, 4)) | |
| Reco_Policy_Cat = st.slider('Recommended Policy Category', min_value=1, max_value=22, value=6, step=1) | |
| submitted = st.form_submit_button("Check") | |
| # Dataframe | |
| data = { | |
| 'Holding_Policy_Duration': Holding_Policy_Duration, | |
| 'Holding_Policy_Type': Holding_Policy_Type, | |
| 'Reco_Policy_Cat': Reco_Policy_Cat, | |
| } | |
| df = pd.DataFrame([data]) | |
| # display dataframe of inputted data | |
| st.dataframe(df) | |
| # show result | |
| if submitted: | |
| result = model.predict(df) | |
| if result == 1: | |
| st.write('Lead will likely become actual customer') | |
| else: | |
| st.write('Lead will not likely become actual customer') | |
| if __name__=='__main__': | |
| run() |