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import streamlit as st
import pandas as pd
import pickle
st.title("Deteksi Kesehatan Jantung Anda")
# import model
model = pickle.load(open('final_pipeline.pkl' , 'rb'))
st.write('Isi kelengkapan data dibawah')
# user input
Age = st.slider(label='Age', min_value=10, max_value=100)
Sex = st.selectbox(label='Gender', options=['M', 'F', 'Non-Binary'])
ChestPainType = st.selectbox(label='ChestPainType', options=['TA', 'ASY', 'NAP', 'ATA'])
RestingBP = st.slider(label='RestingBP', min_value=100, max_value=200, step=1)
Cholesterol = st.slider(label='Cholesterol', min_value=0, max_value=409)
FastingBS = st.selectbox(label='FastingBS', options=[0, 1])
RestingECG = st.slider(label='RestingECG', min_value=0, max_value=300)
MaxHR = st.slider(label='MaxHR', min_value=0, max_value=300)
ExerciseAngina = st.selectbox(label='ExerciseAngina',options=['Y', 'N'])
Oldpeak = st.slider(label='Oldpeak', min_value=0.0, max_value=3.0, step=0.1)
ST_Slope = st.selectbox(label='ST_Slope', options=['Flat', 'Up', 'Down'])
# convert into dataframe
data = pd.DataFrame({'Age': [Age],
'Sex': [Sex],
'ChestPainType': [ChestPainType],
'RestingBP':[RestingBP],
'FastingBS': [FastingBS],
'RestingECG': [RestingECG],
'MaxHR': [MaxHR],
'ExerciseAngina': [ExerciseAngina],
'Oldpeak': [Oldpeak],
'ST_Slope': [ST_Slope]
})
# interpretation
if st.button('Predict'):
classifications = model.predict(data).tolist()[0]
st.write('Prediction Result : ')
if classifications == 0:
st.subheader('Sehat')
elif classifications == 1:
st.subheader('Terindikasi jantung') |