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app.py

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+import pandas as pd
+import numpy as np
+import joblib
+import streamlit as st
+
+with open('pipeline_knn.pkl', 'rb') as file_1:
+  full_imbhandling = joblib.load(file_1)
+
+st.header('Stroke Prediction')
+
+age = st.number_input('Age : ', 1, 82)
+average_glucose_level = st.number_input('Average Glucose Level : ', 55.12, 271.74, step=0.1)
+bmi = st.number_input('BMI : ', 10.3, 97.6, step=0.1)
+hypertension = st.radio('Hypertension : ', (0, 1))
+heart_disease = st.radio('Heart Disease : ', (0, 1))
+ever_married = st.radio('Married Status : ', ('Yes', 'No'))
+smoking_status = st.selectbox('Smoking Status : ', ('formerly smoked', 'never smoked', 'smokes', 'Unknown'))
+
+if st.button('Predict'):
+    data_inf = pd.DataFrame({'age' : [age], 
+                            'avg_glucose_level' : [average_glucose_level], 
+                            'bmi' : [bmi], 
+                            'hypertension' : [hypertension], 
+                            'heart_disease' : [heart_disease], 
+                            'ever_married' : [ever_married], 
+                            'smoking_status' : [smoking_status]})
+
+    hasil = 'Not Stroke' if full_imbhandling.predict(data_inf) == 0 else 'Stroke'
+    st.header(f'Prediksi = {hasil}')

pipeline_knn.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:77afea2bb61e2fdd5e47ed0c047d57de92e13a10562b02ccf2282aa4559da176
+size 1871530