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import streamlit as st
import pandas as pd
import numpy as np
import pickle
import json
import joblib as jb
#load models
model = jb.load('model.pkl')
def run():
with st.form('key=form_prediction') :
age = st.number_input('Age', min_value=40, max_value=95, value= 60, step=1, help='Usia anda')
anaemia = st.selectbox('Anemia',(0,1), index= 1)
creatinine_phosphokinase= st.number_input('creatinine_phosphokinase', min_value=23, max_value=7861)
diabetes = st.selectbox('Diabetes',(0,1), index= 1)
ejection_fraction = st.number_input('ejection_fraction', min_value=14, max_value=80)
high_blood_pressure = st.selectbox('Tekanan Darah',(0,1), index= 1)
platelets = st.number_input('platelets', min_value=25100, max_value=850000)
serum_creatinine = st.number_input('serum creatinine',min_value=0.5,max_value=9.4)
serum_sodium = st.number_input('serum_sodium',min_value=113, max_value=148)
sex = st.selectbox('Jenis Kelamin',(0,1), index= 1)
smoking = st.selectbox('smoking',(0,1), index= 1)
time = st.slider('serum creatinine',4,135,285)
submitted = st.form_submit_button('Predict')
data_inf = {
'age': age,
'anaemia': anaemia,
'creatinine_phosphokinase':creatinine_phosphokinase,
'diabetes':diabetes,
'ejection_fraction': ejection_fraction,
'high_blood_pressure': high_blood_pressure,
'platelets' :platelets,
'serum_creatinine' :serum_creatinine,
'serum_sodium' :serum_sodium,
'sex': sex,
'smoking':smoking,
'time': time
}
data_inf = pd.DataFrame([data_inf])
st.dataframe(data_inf)
if submitted:
# Predict using bagging
y_pred_inf = model.predict(data_inf)
st.write('# Death Prediction : ', str(int(y_pred_inf)))
if __name__=='__main__':
run()
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