The data consists of 270 patients described by six numerical variables and eight categorical variables.
A data frame of 270 rows (patients) and 14 columns (variables):
Numerical. Age in years.
Numerical. Resting blood pressure (in mmHg) at hospital admittance.
Numerical. Maximum heart rate achieved during exercise.
Numerical. ST depression induced by exercise relative to rest.
Numerical. Number of major vessels (0-3) colored by fluoroscopy.
Categorical. Sex (1 = male; 0 = female).
Categorical. 1: typical angina, 2: atypical angina, 3: non-anginal pain, 4: asymptomatic.
Categorical. 1 = true; 0 = false.
Categorical. 0: normal, 1: ST-T wave abnormality (T wave inversions and/or ST elevation or depression >0.05mV), 2: showing probable or definite left ventricular hypertrophy by Estes' criteria.
Categorical. 1 = yes; 0 = no.
Categorical. 1: upsloping, 2: flat, 3: downsloping.
Categorical. 3: normal blood flow, 6: fixed defect, 7: reversible defect.
Categorical. Absence or presence of a heart disease.
A. Frank and A. Asuncion. UCI machine learning repository, statlog (heart) data set, 2010.
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