A disease is an unnatural medical condition that negatively affects the functional state of an organism and is generally associated with certain signs of illness. As reported by World Health Organization (WHO), Heart Disease and Stroke are the world’s biggest killers and have remained the leading causes of death globally in the last 15 years. In the direction of predicting heart disease, Machine Learning can present remarkable features that simplify the identification of unseen patterns, eventually providing clinical insights that assist physicians in planning and providing care.

Data Description:
This data set dates from 1988 and consists of four databases: Cleveland, Hungary, Switzerland, and Long Beach V. It contains 76 attributes, including the predicted attribute, but all published experiments refer to using a subset of 14 of them. The "target" field refers to the presence of heart disease in the patient. It is integer valued 0 = no disease and 1 = disease.


Attribute Information:

age
sex
chest pain type (4 values)
resting blood pressure
serum cholestoral in mg/dl
fasting blood sugar > 120 mg/dl
resting electrocardiographic results (values 0,1,2)
maximum heart rate achieved
exercise induced angina
oldpeak = ST depression induced by exercise relative to rest
the slope of the peak exercise ST segment
number of major vessels (0-3) colored by flourosopy
thal: 0 = normal; 1 = fixed defect; 2 = reversable defect
The names and social security numbers of the patients were recently removed from the database, replaced with dummy values.