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"""Untitled15.ipynb |
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Automatically generated by Colaboratory. |
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Original file is located at |
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https://colab.research.google.com/drive/1LkYVMK8AOEpUsR_FhEmhaVir9hAQSBsg |
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""" |
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import joblib |
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import pandas as pd |
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import streamlit as st |
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smoking_status = {'formerly smoked': 1, |
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'never smoked ': 2, |
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'smokes': 3, |
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'Unknown': 4, |
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} |
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model = joblib.load('model.joblib') |
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unique_values = joblib.load('unique_values.joblib') |
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unique_gender = unique_values["gender"] |
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unique_ever_married = unique_values["ever_married"] |
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unique_work_type = unique_values["work_type"] |
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unique_Residence_type = unique_values["Residence_type"] |
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unique_smoking_status = unique_values["smoking_status"] |
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def main(): |
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st.title("Stoke Analysis") |
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with st.form("questionaire"): |
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age = st.slider("age", min_value=0, max_value=100) |
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gender = st.selectbox("gender", unique_gender) |
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hypertension = st.slider("hypertension", min_value=0, max_value=1) |
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heart_disease = st.slider("heart_disease", min_value=0, max_value=1) |
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ever_married = st.selectbox("ever_married", unique_ever_married) |
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work_type = st.selectbox("work_type", unique_work_type) |
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Residence_type = st.selectbox("Residence_type", unique_Residence_type) |
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avg_glucose_level = st.slider("avg_glucose_level", min_value=0, max_value=300) |
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bmi = st.slider("bmi", min_value=0, max_value=100) |
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smoking_status = st.selectbox("smoking_status", unique_smoking_status) |
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clicked = st.form_submit_button("Predict stroke") |
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if clicked: |
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result=model.predict(pd.DataFrame({"age": [age], |
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"gender": [gender], |
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"hypertension": [hypertension], |
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"heart_disease": [heart_disease], |
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"ever_married": [ever_married], |
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"work_type": [work_type], |
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"Residence_type": [Residence_type], |
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"avg_glucose_level": [avg_glucose_level], |
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"bmi": [bmi], |
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"smoking_status":[smoking_status]})) |
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result = '1' if result[0] == 1 else '0' |
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st.success('The predicted stroke is {}'.format(result)) |
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if __name__=='__main__': |
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main() |
