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7ff9d99 100fb96 7ff9d99 d536865 7ff9d99 bfc7a1e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | import streamlit as st
import pandas as pd
import pickle
st.title("predict patient will death or not")
#import
rf = 'rf_pred.pkl'
rfc = pickle.load(open(rf, 'rb'))
st.write('Insert feature to predict')
age = st.slider(label='age', min_value=0, max_value=200, value=42, step=1)
ane = st.selectbox(label='anemia', options=['0', '1'])
cp = st.slider(label='creatinine_phosphokinase', min_value=0, max_value=1000, value=420, step=1)
dia = st.selectbox(label='diabetes', options=['0', '1'])
ejt = st.slider(label='ejection_fraction', min_value=0, max_value=200, value=42, step=1)
hbp = st.selectbox(label='high_blood_pressure', options=['0', '1'])
pla = st.slider(label='platelets', min_value=100000.0, max_value=999999.0, value=420000.0, step=0.01)
sc = st.slider(label='serum_creatinine', min_value=0.0, max_value=99.9, value=42.0, step=0.1)
ss = st.slider(label='serum_sodium', min_value=0, max_value=999, value=42, step=1)
sex = st.selectbox(label='sex', options=['0', '1'])
smk = st.selectbox(label='smoking', options=['0', '1'])
tym = st.slider(label='time', min_value=0, max_value=999, value=42, step=1)
# color = st.number_input(label='Colour', min_value=240, max_value=255, value=245, step=1)
# convert into dataframe
data = pd.DataFrame({'age': [age],
'anemia': [ane],
'creatinine_phosphokinase': [cp],
'diabetes':[dia],
'ejection_fraction': [ejt],
'high_blood_pressure': [hbp],
'platelets': [pla],
'serum_creatinine': [sc],
'serum_sodium': [ss],
'sex': [sex],
'smoking': [smk],
'time': [tym]})
# model predict
death = rfc.predict(data).tolist()[0]
# interpretation
st.write('Predition Result: ')
if death == 0:
st.text('yeh masih hidup')
else:
st.text('innalilahi wa inna ilaihi rajiun')
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