Diagnostic attributes of patients classified as having heart disease or not.
270 observations from 17 variables represented as a list consisting
of a binary factor response vector
with levels 'absence' and 'presence' indicating the absence or presence of
heart disease and
x: a sparse feature matrix of class 'dgCMatrix' with the
diastolic blood pressure
serum cholesterol in mg/dl
maximum heart rate achieved
ST depression induced by exercise relative to rest
the number of major blood vessels (0 to 3) that were colored by fluoroscopy
sex of the participant: 0 for male, 1 for female
a dummy variable indicating whether the person suffered angina-pectoris during exercise
indicates a fasting blood sugar over 120 mg/dl
indicates a ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV)
probable or definite left ventricular hypertrophy by Estes' criteria
a flat ST curve during peak exercise
a downwards-sloping ST curve during peak exercise
The original dataset contained 13 variables. The nominal of these were
dummycoded, removing the first category. No precise information regarding
ecg could be found, which explains
their obscure definitions here.
Dua, D. and Karra Taniskidou, E. (2017). UCI Machine Learning Repository http://archive.ics.uci.edu/ml. Irvine, CA: University of California, School of Information and Computer Science.
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