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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()
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