This project aims to generate a model to predict the presence of a heart disease. The UCI heart disease database contains 76 attributes, but all published experiments refer to using a subset of 14. The target attribute is an integer valued from 0 (no presence) to 4. However, for sake of simplicity it will be reduced to binary classification, i.e, 0
vs 0 <
.
The authors of the databases: Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D.
Description | Variable | Type | |
---|---|---|---|
age | age in years | continuous | int |
sex | 1 = male, 0 = female | categorial | int |
cp | chest pain type: 1: typical angina, 2: atypical angina, 3: non-anginal pain, 4: asymptomatic | categorial | int |
trestbps | resting blood pressure in mm Hg | continuous | float |
chol | serum cholestoral in mg/dl | continuous | float |
fbs | fasting blood sugar > 120 mg/dl: 1 = true, 0 = false | categorial | int |
restecg | 0: normal, 1: having ST-T wave abnormality, 2: left ventricular hypertrophy | categorial | int |
thalach | maximum heart rate achieved | continuous | float |
exang | exercise induced angina (1 = yes; 0 = no) | categorial | int |
oldpeak | ST depression induced by exercise relative to rest | continuous | float |
slope | the slope of the peak exercise ST segment: 1: upsloping, 2: flat, 3: downsloping | categorial | int |
ca | number of major vessels: (0-3) colored by flourosopy | continuous | int |
thal | 3: normal, 6: fixed defect, 7: reversable defect | categorial | int |
target | diagnosis of heart disease: (0 = false, 1 = true | categorial | int |
Data fetching --> Wrangling --> Data analysis --> Modeling --> evaluation