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import joblib
import pandas as pd
import streamlit as st
import category_encoders as ce
model = joblib.load('model_tree.joblib')
unique_values = joblib.load('unique_values.joblib')
SEX_DICT = {'M':1,
'F':2}
BP_DICT = {'LOW':1,
'NORMAL':2,
'HIGH':3}
Cholesterol_DICT = {'NORMAL':1,
'HIGH':2}
unique_Sex = unique_values['Sex']
unique_BP = unique_values['BP']
unique_Cholesterol = unique_values['Cholesterol']
def main():
st.title("Medicine Suggestion") #<-Apps' name
with st.form("questionaire"):
Age = st.slider('Age',min_value=10,max_value=100)
Na_to_K = st.slider('Na_to_K',min_value=1,max_value=50)
Sex = st.selectbox('Sex',options=unique_Sex)
BP = st.selectbox('BP',options=unique_BP)
Cholesterol = st.selectbox('Cholesterol',options=unique_Cholesterol)
# clicked==True only when the button is clicked
clicked = st.form_submit_button("Predict medicine")
if clicked:
result=model.predict(pd.DataFrame({"Age": [Age],
"Na_to_K": [Na_to_K],
"Sex": [SEX_DICT[Sex]],
"BP": [BP_DICT[BP]],
"Cholesterol": [Cholesterol_DICT[Cholesterol]]
}))
# Show prediction
result = result[0]
st.success("You should get " +result)
# Run main()
if __name__=="__main__":
main() |