Update app.py

app.py

@@ -7,9 +7,7 @@ model = load('loandefaulter.joblib')
 scaler = load('scaler.joblib')
 
 # Define numerical features for scaling
-num_features = [
-    'loan_amnt', 'int_rate', 'installment', 'annual_inc', 'dti', 'revol_bal', 'revol_util', 'total_acc', 'mort_acc'
-]
+num_features = ['loan_amnt', 'int_rate', 'installment', 'annual_inc', 'cibil_score']
 
 # Create the Streamlit app
 st.set_page_config(page_title='Loan Default Prediction', layout='wide')
@@ -29,13 +27,9 @@ st.markdown("""
 # Input fields with sliders
 loan_amnt = st.slider('Loan Amount', min_value=0.0, max_value=1000000.0, step=1000.0, value=10000.0)
 int_rate = st.slider('Interest Rate (%)', min_value=0.0, max_value=30.0, step=0.1, value=5.0)
-installment = st.slider('Installment', min_value=0.0, max_value=10000.0, step=10.0, value=200.0)
+installment = st.slider('EMI Amount', min_value=0.0, max_value=10000.0, step=10.0, value=200.0)
 annual_inc = st.slider('Annual Income', min_value=0.0, max_value=1000000.0, step=1000.0, value=50000.0)
-dti = st.slider('Debt-to-Income Ratio', min_value=0.0, max_value=100.0, step=0.1, value=15.0)
-revol_bal = st.slider('Revolving Balance', min_value=0.0, max_value=500000.0, step=100.0, value=10000.0)
-revol_util = st.slider('Revolving Utilization (%)', min_value=0.0, max_value=100.0, step=0.1, value=30.0)
-total_acc = st.slider('Total Accounts', min_value=0, max_value=100, step=1, value=10)
-mort_acc = st.slider('Mortgage Accounts', min_value=0, max_value=10, step=1, value=1)
+cibil_score = st.number_input('CIBIL Score', min_value=300, max_value=900, step=1, value=700)
 loan_amnt_by_income = loan_amnt / (annual_inc + 1)
 
 # Create a DataFrame for the input
@@ -44,11 +38,7 @@ input_data = pd.DataFrame({
     'int_rate': [int_rate],
     'installment': [installment],
     'annual_inc': [annual_inc],
-    'dti': [dti],
-    'revol_bal': [revol_bal],
-    'revol_util': [revol_util],
-    'total_acc': [total_acc],
-    'mort_acc': [mort_acc]
+    'cibil_score': [cibil_score]
 })
 
 # Scale the numerical features that were used to fit the scaler
@@ -65,3 +55,4 @@ if st.button('Predict'):
     st.markdown(f"""
         <div style="font-size: 24px; color: {color}; font-weight: bold;">Prediction: {result}</div>
     """, unsafe_allow_html=True)
+