Spaces:
Sleeping
Sleeping
| import numpy as np | |
| import pickle | |
| import streamlit as st | |
| # loading the saved model | |
| loaded_model = pickle.load(open('rf_class.sav', 'rb')) | |
| # creating a function for Prediction | |
| def diabetes_prediction(input_data): | |
| # changing the input_data to numpy array | |
| input_data_as_numpy_array = np.asarray(input_data) | |
| # reshape the array as we are predicting for one instance | |
| input_data_reshaped = input_data_as_numpy_array.reshape(1,-1) | |
| prediction = loaded_model.predict(input_data_reshaped) | |
| if prediction[0] == 0: | |
| return 'Bad' | |
| else: | |
| return 'Good' | |
| def main(): | |
| # giving a title | |
| st.title('Risk Credit Prediction Web App') | |
| st.title('Enter numeric data only!. Use examples.') | |
| # getting the input data from the user | |
| Age = st.text_input('Age (example >>> 19-75)') | |
| Sex = st.text_input('Sex (example >>> male=1 female=0)') | |
| Job = st.text_input('Job (example >>> 2, 1, 3, 0)') | |
| Housing = st.text_input('Housing (example >>> own=3, free=2, rent=1)') | |
| Saving_accounts = st.text_input('Saving accounts (example >>> moderate=1, little=0, quite rich=3, rich=2)') | |
| Checking_account = st.text_input('Checking account (example >>> little=1, moderate=2, rich=3)') | |
| Credit_amount = st.text_input('Credit amount (example >>> 100-20 000 (Deutsch Mark))') | |
| Duration = st.text_input('Duration (example >>> 4-60 (month))') | |
| Purpose = st.text_input('Purpose (example >>> radio/TV = 0, education = 1, furniture/equipment = 2, car = 3, business = 4,domestic_appliances = 5, repairs = 6, vacation/others = 7)') | |
| # code for Prediction | |
| risk = '' | |
| # creating a button for Prediction | |
| if st.button('Submit'): | |
| risk = diabetes_prediction([Age, Sex, Job, Housing, Saving_accounts, Checking_account, Credit_amount, Duration, Purpose]) | |
| st.success(risk) | |
| if __name__ == '__main__': | |
| main() | |