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A heart disease prediction classifier based on the Cleveland Database. The objective is to predict the presence of heart disease.

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This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4.

Attribute Information:

  1. age
  2. sex
  3. chest pain type (4 values)
  4. resting blood pressure
  5. serum cholestoral in mg/dl
  6. fasting blood sugar > 120 mg/dl
  7. resting electrocardiographic results (values 0,1,2)
  8. maximum heart rate achieved
  9. exercise induced angina
  10. oldpeak = ST depression induced by exercise relative to rest
  11. the slope of the peak exercise ST segment
  12. number of major vessels (0-3) colored by flourosopy
  13. thal: 3 = normal; 6 = fixed defect; 7 = reversable defect
  14. target: 0 = absence ; 1 = presence

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A heart disease prediction classifier based on the Cleveland Database. The objective is to predict the presence of heart disease.

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