|
from ssl import Options |
|
import joblib |
|
import pandas as pd |
|
import streamlit as st |
|
|
|
|
|
model = joblib.load('model.joblib') |
|
unique_values = joblib.load('unique_values(1).joblib') |
|
|
|
|
|
|
|
unique_fea_1 = unique_values["fea_1"] |
|
unique_fea_2 = unique_values["fea_2"] |
|
unique_fea_3 = unique_values["fea_3"] |
|
unique_fea_4 = unique_values["fea_4"] |
|
unique_fea_5 = unique_values["fea_5"] |
|
unique_fea_6 = unique_values["fea_6"] |
|
unique_fea_7 = unique_values["fea_7"] |
|
unique_fea_8 = unique_values["fea_8"] |
|
unique_fea_9 = unique_values["fea_9"] |
|
unique_fea_10 = unique_values["fea_10"] |
|
unique_fea_11 = unique_values["fea_11"] |
|
|
|
|
|
def main(): |
|
st.title("Customer check risk") |
|
|
|
with st.form("questionaire"): |
|
fea1 = st.selectbox(options =unique_fea_1 ) |
|
fea3 = st.selectbox(options =unique_fea_3) |
|
fea5 = st.selectbox(options =unique_fea_5 ) |
|
fea6 = st.selectbox(options =unique_fea_6 ) |
|
fea7 = st.selectbox(options =unique_fea_7 ) |
|
fea9 = st.selectbox(options =unique_fea_9 ) |
|
|
|
|
|
clicked = st.form_submit_button("risk") |
|
if clicked: |
|
result=model.predict(pd.DataFrame({"fea1": [fea1], |
|
"fea3": [fea3], |
|
"fea5": [fea5], |
|
"fea6": [fea6], |
|
"fea7": [fea7], |
|
"fea9": [fea9] |
|
})) |
|
|
|
if result==1: |
|
result='the customer is in high credit risk' |
|
else : |
|
result='the customer is in low credit risk' |
|
st.success('Your risk is '+result) |
|
|
|
if __name__=='__main__': |
|
main() |
