Upload 5 files

.gitignore

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+good_model.pkl
+Heart_Attack_Rist_Predictor with Eval ML.ipynb

app.py

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+import streamlit as st
+import numpy as np
+import joblib as jl
+# Initialize your trained model
+model = jl.load('best_model.pkl')
+
+#Define the layout of the web application
+st.title("Heart Attack Risk Prediction")
+st.markdown("Enter the following information to predict your risk of a heart attack.")
+
+# Define the user input fields
+age = st.number_input("Age", min_value=1, max_value=120, value=30)
+sex = st.selectbox("Sex", ["Male", "Female"])
+cp = st.selectbox("Chest Pain Type", [0, 1, 2, 3])
+trtbps = st.number_input("Resting Blood Pressure", min_value=1, max_value=300, value=120)
+chol = st.number_input("Serum Cholesterol", min_value=1, max_value=1000, value=200)
+fbs = st.selectbox("Fasting Blood Sugar > 120 mg/dl", [0, 1])
+restecg = st.selectbox("Resting Electrocardiographic Results", [0, 1, 2])
+thalachh = st.number_input("Maximum Heart Rate Achieved", min_value=1, max_value=300, value=150)
+exng = st.selectbox("Exercise Induced Angina", [0, 1])
+#oldpeak = st.number_input("ST Depression Induced by Exercise", min_value=0.0, max_value=10.0, value=0.0)
+#slp = st.selectbox("Slope of the Peak Exercise ST Segment", [0, 1, 2])
+caa = st.number_input("Number of Major Vessels Colored by Flourosopy", min_value=0, max_value=4, value=0)
+#thal = st.selectbox("Thalassemia", [0, 1, 2, 3])
+
+# Define the predict button
+if st.button("Predict"):
+    # Preprocess the user input
+    sex = 1 if sex == "Male" else 0
+    input_data = np.array([[age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, caa]])
+
+    # Make a prediction on the user input
+    prediction = model.predict(input_data)
+
+    # Display the prediction to the user
+    if prediction == 0:
+        st.markdown("### Result: **Low Risk** of a Heart Attack")
+    else:
+        st.markdown("### Result: **High Risk** of a Heart Attack")

best_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d61307ce80e85c35b1190293bb91378d1180fb18453e893716c89aa8411b78ca
+size 948

heart.csv

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requirements.txt

@@ -0,0 +1,52 @@
+altair==4.2.2
+attrs==22.2.0
+blinker==1.5
+cachetools==5.3.0
+certifi==2022.12.7
+charset-normalizer==3.0.1
+click==8.1.3
+colorama==0.4.6
+decorator==5.1.1
+entrypoints==0.4
+gitdb==4.0.10
+GitPython==3.1.30
+idna==3.4
+importlib-metadata==6.0.0
+Jinja2==3.1.2
+joblib==1.2.0
+jsonschema==4.17.3
+markdown-it-py==2.1.0
+MarkupSafe==2.1.2
+mdurl==0.1.2
+numpy==1.24.2
+packaging==23.0
+pandas==1.5.3
+Pillow==9.4.0
+protobuf==3.20.3
+pyarrow==11.0.0
+pydeck==0.8.0
+Pygments==2.14.0
+Pympler==1.0.1
+pyrsistent==0.19.3
+python-dateutil==2.8.2
+pytz==2022.7.1
+pytz-deprecation-shim==0.1.0.post0
+requests==2.28.2
+rich==13.3.1
+scikit-learn==1.2.1
+scipy==1.10.0
+semver==2.13.0
+six==1.16.0
+smmap==5.0.0
+streamlit==1.18.1
+threadpoolctl==3.1.0
+toml==0.10.2
+toolz==0.12.0
+tornado==6.2
+typing_extensions==4.5.0
+tzdata==2022.7
+tzlocal==4.2
+urllib3==1.26.14
+validators==0.20.0
+watchdog==2.2.1
+zipp==3.13.0