Machine Learning Model Implemented

Stroke Prediction/deploy.py

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+import streamlit as st
+import joblib
+import os
+import random
+
+# Directory to load the models
+model_dir = "saved_models"
+
+# Load the models
+lrClassifier = joblib.load(os.path.join(model_dir, 'logistic_regression_model.pkl'))
+nbClassifier = joblib.load(os.path.join(model_dir, 'naive_bayes_model.pkl'))
+
+# Function to make predictions
+def make_prediction(features):
+    predictions = {
+        "Logistic Regression": lrClassifier.predict([features])[0],
+        "Naive Bayes": nbClassifier.predict([features])[0],
+    }
+    return predictions
+
+# List of healthy life quotes
+healthy_life_quotes = [
+    "Eat a balanced diet.",
+    "Exercise regularly.",
+    "Get enough sleep.",
+    "Stay hydrated.",
+    "Practice mindfulness.",
+    "Avoid smoking.",
+    "Limit alcohol intake.",
+    "Maintain a healthy weight.",
+    "Stay socially connected.",
+    "Get regular medical check-ups."
+]
+
+# Initialize session state for theme
+if 'theme' not in st.session_state:
+    st.session_state['theme'] = 'light'
+
+# Function to toggle theme
+def toggle_theme():
+    if st.session_state['theme'] == 'light':
+        st.session_state['theme'] = 'dark'
+    else:
+        st.session_state['theme'] = 'light'
+
+# Apply CSS based on the theme
+if st.session_state['theme'] == 'light':
+    page_bg_img = '''
+    <style>
+    .stApp {
+        background: rgba(255, 255, 255, 0.8);
+        color: #000000;
+        padding: 20px;
+        border-radius: 10px;
+    }
+    .stButton>button {
+        background-color: #4CAF50;
+        color: white;
+        border-radius: 12px;
+        padding: 10px 24px;
+        border: none;
+    }
+    .stButton>button:hover {
+        background-color: #45a049;
+    }
+    </style>
+    '''
+else:
+    page_bg_img = '''
+    <style>
+    .stApp {
+        background: rgba(0, 0, 0, 0.7);
+        color: #ffffff;
+        padding: 20px;
+        border-radius: 10px;
+    }
+    .stButton>button {
+        background-color: #4CAF50;
+        color: white;
+        border-radius: 12px;
+        padding: 10px 24px;
+        border: none;
+    }
+    .stButton>button:hover {
+        background-color: #45a049;
+    }
+    </style>
+    '''
+
+st.markdown(page_bg_img, unsafe_allow_html=True)
+
+# Sidebar inputs
+st.sidebar.title('Prediction Details')
+
+gender = st.sidebar.selectbox('Gender', ('Male', 'Female'))
+age = st.sidebar.slider('Age', 0, 100)
+glucose_level = st.sidebar.slider('Glucose Level', 0, 300)
+bmi = st.sidebar.slider('BMI (Body Mass Index)', 18, 30)
+hypertension = st.sidebar.radio('Hypertension', ("Yes", "No"))
+heart_disease = st.sidebar.radio('Heart Disease', ("Yes", "No"))
+work_type = st.sidebar.radio('Work Type', ('Private', 'Self Employed', 'Government job', 'Children', 'Never Worked'))
+
+# Map inputs to features
+gender_map = {'Male': 0, 'Female': 1}
+hypertension_map = {'Yes': 1, 'No': 0}
+heart_disease_map = {'Yes': 1, 'No': 0}
+work_type_map = {'Private': 0, 'Self Employed': 1, 'Government job': 2, 'Children': 3, 'Never Worked': 4}
+
+features = [
+    gender_map[gender],
+    age,
+    hypertension_map[hypertension],
+    heart_disease_map[heart_disease],
+    work_type_map[work_type],
+    glucose_level,
+    bmi
+]
+
+# Main page title and header
+st.title("Brain Stroke Prediction Tool")
+st.header("Input Parameters")
+
+# Theme toggle button
+if st.sidebar.button('Toggle Theme'):
+    toggle_theme()
+
+# Predict button
+if st.button('Predict'):
+    predictions = make_prediction(features)
+    st.subheader("Predictions")
+    for model, prediction in predictions.items():
+        st.write(f"{model}: {'Stroke' if prediction == 1 else 'No Stroke'}")
+
+# Button for healthy life quotes
+if st.button('Get Healthy Life Quote'):
+    quote = random.choice(healthy_life_quotes)
+    st.subheader("Healthy Life Quote")
+    st.write(quote)

Stroke Prediction/saved_models/neural_network_model.pkl

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+�