import joblib import pandas as pd import streamlit as st model = joblib.load('rf.joblib') unique_values = joblib.load('unique_values1.joblib') unique_sex = unique_values["Gender"] unique_occupation = unique_values["Occupation"] unique_ฺBMI = unique_values["BMI Category"] unique_Blood = unique_values["Blood Pressure"] def main(): st.title("Sleeping Health") with st.form("questionaire"): Gender = st.selectbox("Gender", unique_sex) age = st.slider("Age", min_value=1, max_value=100) occupation = st.selectbox("Occupation", unique_occupation) Sleep_Duration = st.slider("Sleep Duration", min_value=0, max_value=24) Quality_of_Sleep = st.slider("Quality of Sleep", min_value=1, max_value=10) Physical_Activity_Level = st.slider("Quality of Sleep", min_value=0, max_value=1440) BMI_Category = st.selectbox("ฺBMI Category", unique_ฺBMI) Blood_Pressure = st.selectbox("Blood Pressure", unique_Blood) Heart_Rate = st.slider("Heart Rate", min_value=60, max_value=100) Daily_Steps = st.slider("Daily Steps", min_value=3000, max_value=10000) clicked = st.form_submit_button("Predict Sleep Health") if clicked: result=model.predict(pd.DataFrame({"age": [age], "Gender": [Gender], "Occupation": [occupation], "Sleep Duration (hours)": [Sleep_Duration], "Quality of Sleep (scale: 1-10)": [Quality_of_Sleep], "Physical Activity Level (minutes/day)": [Physical_Activity_Level], "BMI Category": [BMI_Category], "Blood Pressure (systolic/diastolic)": [Blood_Pressure], "Heart Rate (bpm)": [Heart_Rate], "Daily Steps": [Daily_Steps] })) if result[0] == 0: result_message = "No Sleep Disorder" elif result[0] == 1: result_message = "Insomnia" elif result[0] == 2: result_message = "Sleep Apnea" st.success(result_message) if __name__=='__main__': main()