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import numpy as np |
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import pandas as pd |
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import matplotlib.pyplot as plt |
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import seaborn as sns |
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from sklearn.linear_model import LogisticRegression |
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from sklearn.neighbors import KNeighborsClassifier |
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from sklearn.metrics import accuracy_score |
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df = pd.read_csv('Sleep_health_and_lifestyle_dataset.csv') |
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df.isnull().sum() |
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df['Sleep Disorder'].fillna('None', inplace=True) |
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df.drop('Person ID', axis=1, inplace=True) |
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df['systolic_bp'] = df['Blood Pressure'].apply(lambda x: x.split('/')[0]) |
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df['diastolic_bp'] = df['Blood Pressure'].apply(lambda x: x.split('/')[1]) |
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df.drop('Blood Pressure', axis=1, inplace=True) |
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df['BMI Category'] = df['BMI Category'].replace('Normal Weight', 'Normal') |
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df['Gender'].replace({'Male':0, 'Female':1}, inplace=True) |
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df['Occupation'].replace({'Software Engineer':0, 'Doctor':1,'Sales Representative':2,'Teacher':3,'Nurse':4,'Engineer':5,'Accountant':6,'Scientist':7,'Lawyer':8,'Salesperson':9,'Manager':10}, inplace=True) |
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df['BMI Category'].replace({'Normal':0, 'Overweight':1, 'Obese':2}, inplace=True) |
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df['Sleep Disorder'].replace({'None':0,'Insomnia':1, 'Sleep Apnea':2}, inplace=True) |
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from sklearn.model_selection import train_test_split |
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X_train, X_test, y_train, y_test = train_test_split(df.drop('Sleep Disorder',axis=1), df['Sleep Disorder'], test_size=0.2, random_state=42) |
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from sklearn.ensemble import RandomForestClassifier |
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rfc = RandomForestClassifier() |
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rfc.fit(X_train, y_train) |
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def func(a, b, c, d, e, f, g, h, i, j, k, l): |
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x_test = [[a, b, c, d, e, f, g, h, i, j, k, l]] |
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result = rfc.predict(x_test)[0] |
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dict = { |
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0 : "None", |
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1: "Insomnia", |
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2 : "Sleep Apnea" |
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} |
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if result==0: |
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str = "Yay! You are totally fit 😃😎" |
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elif result==1: |
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str = "You may be suffering from Sleep Insomnia 😐😐" |
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else: |
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str="You may be suffering from Sleep Apnea 🙁🙁" |
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return f"{dict[result]}\n\n{str}" |
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import gradio as gr |
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demo = gr.Interface( |
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fn= func, |
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inputs=[ |
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gr.Textbox(label="Gender", placeholder="Enter 0 for Male and 1 for Female", elem_id="gender",type='text'), |
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gr.Textbox(label="Age", placeholder="Enter Your Age", elem_id="gender",type='text'), |
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gr.Textbox(label="Occupation", placeholder="Enter from 0 - 10", elem_id="gender",type='text'), |
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gr.Textbox(label="Sleep Duration(in Hrs)", placeholder="Enter Your Sleep Duration", elem_id="gender",type='text'), |
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gr.Textbox(label="Quality of Sleep", placeholder="Enter Your Quality of Sleep", elem_id="gender",type='text'), |
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gr.Textbox(label="Physical Activity Level", placeholder="Enter Your Physical Activity Level", elem_id="gender",type='text'), |
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gr.Textbox(label="Stress Level", placeholder="Enter Your Stress Level", elem_id="gender",type='text'), |
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gr.Textbox(label="BMI Category", placeholder="Enter 0 for Normal 1 for Overweight and 2 for Obeses", elem_id="gender",type='text'), |
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gr.Textbox(label="Systolic Blood Pressure", placeholder="Enter Your Systolic Blood Pressure", elem_id="gender",type='text'), |
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gr.Textbox(label="Diastolic Blood Pressure", placeholder="Enter Your Diastolic Blood Pressure", elem_id="gender",type='text'), |
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gr.Textbox(label="Heart Rate", placeholder="Enter Your Heart Rate", elem_id="gender",type='text'), |
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gr.Textbox(label="Daily Steps Count", placeholder="Enter Your Daily Steps Count", elem_id="gender",type='text') |
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], |
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outputs='text', |
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theme=gr.themes.Soft(), |
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title="<h1 id=title-first> Welcome to HEALTHSURE <br> <span id=title-second>Predict Your Sleep Disorder here using a ML Model</span> </h1>", |
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description="<p id=desc>◾ Please Enter the Data in following way(Important)<br>◾ Gender: <span id=desc-info>Male=0 Female=1</span><br>◾ Occupation: <span id=desc-info> Software Engineer=0 Doctor=1 Sales Representative=2 Teacher=3 Nurse=4 <br> Engineer=5 Accontant=6 Scientist=7 Lawyer=8 SalesPerson=9 Manager=10</span> <br>◾ BMI Category: <span id=desc-info>Normal=0 OverWeight=1 Obese=2 </span></p> <br> <p id=desc>**Some Examples are given at bottom You can try them by clicking on it.<br>**Enter only Numeric Value</p>", |
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css=""" |
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.gradio-container {background-color: #daeefe}" |
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#gender { background-color : teal !important; } |
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#gender textarea {background-color: #ecf7fd; font-size : 15px; color : black; |
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font-weight : bold; !important;} |
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#desc {font-weight : bold; color : black !important;} |
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#desc-info{font-weight:normal;} |
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h1 {text-align : center; font-size: 40px !important;} |
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#title-first {color:black; !important;} |
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#title-second {color:green; font-size: 17px !important;} |
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#a-tag { color : white !important;} |
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#a-tag:hover {text-decoration : none !important;} |
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""", |
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examples=[[0, 44, 9, 6.3, 6, 45, 7, 1, 130,85, 72, 6000],[1, 31, 4, 7.9, 8, 75, 4, 0, 117, 76, 69, 6800],[1, 49, 4, 6.1, 6, 90, 8, 1, 140,95, 75, 10000]] |
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) |
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demo.launch(inline=False) |
