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app.py

@@ -42,6 +42,26 @@ input_data = pd.DataFrame([{
 # Set classification threshold
 classification_threshold = 0.5
 
+# Correction made to the codes
+
+input_df = pd.DataFrame([input_data])
+
+categorical_cols = [
+    'Partner',          # Whether the customer has a partner (Yes/No)
+    'Dependents',       # Whether the customer has dependents (Yes/No)
+    'PhoneService',     # Whether the customer has phone service (Yes/No)
+    'InternetService',  # Type of internet service (DSL, Fiber optic, No)
+    'Contract',         # Type of contract (Month-to-month, One year, Two year)
+    'PaymentMethod',    # Customer's preferred payment method
+    # same as training
+]
+
+input_df[categorical_cols] = (
+    input_df[categorical_cols]
+    .astype(str)
+    .fillna("missing")
+)
+
 # Predict button
 if st.button("Predict"):
     prediction_proba = model.predict_proba(input_data)[0, 1]