heart | R Documentation |
Predict heart disease from lab data
heart
A data frame with 303 rows and 14 variables:
age
integer. age in years.
sex
factor with 2 levels. male, female.
cp
factor with 4 levels. chest pain type (typical angina, atypical angina, non-anginal pain, asymptomatic).
testbps
integer. resting blood pressure in mm Hg on admission to the hospital.
chol
integer. serum cholestoral in mg/dl.
fbs
integer. fasting blood sugar > 120 mg/dl (1 = true; 0 = false).
restecg
factor with 3 levels. resting electrocardiographic results (normal, having ST-T wave abnormality,left ventricular hypertrophy).
thalach
integer. maximum heart rate achieved.
exang
integer. exercise induced angina (1 = yes; 0 = no).
oldpeak
double. ST depression induced by exercise relative to rest.
slope
factor with 3 levels. the slope of the peak exercise ST segment (upslope, flat, downsloping).
ca
integer. number of major vessels (0-3) colored by flourosopy.
thal
factor with 3 levels. normal, fixed defect, reversable defect.
disease
factor with 2 levels. heart disease (yes, no). This is the outcome variable of interest.
Data obtained from the UCI Machine Learning Repository.
Creators:
Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.
University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.
University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.
V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D.
Donor: David W. Aha (aha '@' ics.uci.edu) (714) 856-8779
summary(heart)
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