Update app.py

app.py

@@ -56,14 +56,6 @@ def main():
 
     # Predict button
     if st.button("Predict"):
-        # Convert numerical features to strings
-        age = str(age)
-        monthly_income = str(monthly_income)
-        num_companies_worked = str(num_companies_worked)
-        percent_salary_hike = str(percent_salary_hike)
-        training_times_last_year = str(training_times_last_year)
-        years_since_last_promotion = str(years_since_last_promotion)
-        years_with_curr_manager = str(years_with_curr_manager)
 
         # Create a DataFrame to hold the user input data
         input_data = pd.DataFrame({
@@ -92,15 +84,6 @@ def main():
         # Make predictions
         prediction = model.predict(input_data)
         probability = model.predict_proba(input_data)[:, 1]
-
-        # Convert integer inputs to integers
-        age = int(age)
-        monthly_income = int(float(monthly_income))
-        num_companies_worked = float(num_companies_worked)
-        percent_salary_hike = int(percent_salary_hike)
-        training_times_last_year = int(training_times_last_year)
-        years_since_last_promotion = int(years_since_last_promotion)
-        years_with_curr_manager = int(years_with_curr_manager)
         
         # Display characteristic-based recommendations
         st.subheader("Suggestions for retaining the employee:")