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A machine learning model is capable of predicting whether or not someone has heart disease based on their medical attributes.
The procedure is as follows :
Problem definition
Data
Evaluation
Features
Modelling
Experimentation
- age- age in years
- sex- (1 = male; 0 = female)
- cp- chest pain type
- trestbps- resting blood pressure (in mm Hg on admission to the hospital)
- chol- serum cholestoral in mg/dl
- fbs- (fasting blood sugar > 120 mg/dl) (1 = true; 0 = false)
- restecg- resting electrocardiographic results
- thalach- maximum heart rate achieved
- exang- exercise induced angina (1 = yes; 0 = no)
- oldpeak- ST depression induced by exercise relative to rest
- slope- the slope of the peak exercise ST segment
- ca- number of major vessels (0-3) colored by flourosopy
- thal- 3 = normal; 6 = fixed defect; 7 = reversable defect
- target- 1 or 0
