#' @title Heart disease
#'
#' @description
#' Predict heart disease from lab data
#'
#' @source
#' Data obtained from the \href{https://archive.ics.uci.edu/ml/datasets/Heart+Disease}{UCI Machine Learning Repository}.
#'
#' Creators:
#'
#' \enumerate{
#' \item Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.
#' \item University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.
#' \item University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.
#' \item 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
#'
#' @format A data frame with 303 rows and 14 variables:
#' \describe{
#' \item{\code{age}}{integer. age in years.}
#' \item{\code{sex}}{factor with 2 levels. male, female.}
#' \item{\code{cp}}{factor with 4 levels. chest pain type (typical angina,
#' atypical angina, non-anginal pain, asymptomatic).}
#' \item{\code{testbps}}{integer. resting blood pressure in mm Hg on admission to the hospital.}
#' \item{\code{chol}}{integer. serum cholestoral in mg/dl.}
#' \item{\code{fbs}}{integer. fasting blood sugar > 120 mg/dl (1 = true; 0 = false).}
#' \item{\code{restecg}}{factor with 3 levels. resting electrocardiographic results (normal,
#' having ST-T wave abnormality,left ventricular hypertrophy).}
#' \item{\code{thalach}}{integer. maximum heart rate achieved.}
#' \item{\code{exang}}{integer. exercise induced angina (1 = yes; 0 = no).}
#' \item{\code{oldpeak}}{double. ST depression induced by exercise relative to rest.}
#' \item{\code{slope}}{factor with 3 levels. the slope of the peak exercise ST segment (upslope, flat, downsloping).}
#' \item{\code{ca}}{integer. number of major vessels (0-3) colored by flourosopy.}
#' \item{\code{thal}}{factor with 3 levels. normal, fixed defect, reversable defect.}
#' \item{\code{disease}}{factor with 2 levels. heart disease (yes, no). This is the outcome variable of interest.}
#' }
#' @examples
#' summary(heart)
"heart"
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