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# -*- coding: utf-8 -*-
"""Untitled15.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1LkYVMK8AOEpUsR_FhEmhaVir9hAQSBsg
"""
import joblib
import pandas as pd
import streamlit as st
smoking_status = {'formerly smoked': 1,
'never smoked ': 2,
'smokes': 3,
'Unknown': 4,
}
model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
unique_gender = unique_values["gender"]
unique_ever_married = unique_values["ever_married"]
unique_work_type = unique_values["work_type"]
unique_Residence_type = unique_values["Residence_type"]
unique_smoking_status = unique_values["smoking_status"]
def main():
st.title("Adult Income Analysis")
with st.form("questionaire"):
age = st.slider("age", min_value=0, max_value=100)
gender = st.selectbox("gender", unique_gender)
hypertension = st.slider("hypertension", min_value=0, max_value=1)
heart_disease = st.slider("heart_disease", min_value=0, max_value=1)
ever_married = st.selectbox("ever_married", unique_ever_married)
work_type = st.selectbox("work_type", unique_work_type)
Residence_type = st.selectbox("Residence_type", unique_Residence_type)
avg_glucose_level = st.slider("avg_glucose_level", min_value=0, max_value=300)
bmi = st.slider("bmi", min_value=0, max_value=100)
smoking_status = st.selectbox("smoking_status", unique_smoking_status)
clicked = st.form_submit_button("Predict stroke")
if clicked:
result=model.predict(pd.DataFrame({"age": [age],
"gender": [gender],
"hypertension": [hypertension],
"heart_disease": [heart_disease],
"ever_married": [ever_married],
"work_type": [work_type],
"Residence_type": [Residence_type],
"avg_glucose_level": [avg_glucose_level],
"bmi": [bmi],
"smoking_status":[smoking_status]}))
result = '1' if result[0] == 1 else '0'
st.success('The predicted stroke is {}'.format(result))
if __name__=='__main__':
main() |