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#' Breast Cancer Wisconsin (Diagnostic)
#'
#' The \code{breast_cancer} Wisconsin data has 569 rows and 31 columns. The
#' first 30 variables report the features that are computed from a digitized
#' image of a fine needle aspirate (FNA) of a breast mass. They describe
#' characteristics of the cell nuclei present in the image. The last column
#' indicates the class labels (Benign = 0 or Malignant = 1).
#'
#' @format A data frame of 569 observations and 31 variables.
#'
#' @examples
#' data(breast_cancer)
#' summary(breast_cancer)
#'
#' @source
#' Wolberg, W., Mangasarian, O., Street, N., & Street, W. (1993).
#' Breast Cancer Wisconsin (Diagnostic).
#' UCI Machine Learning Repository.
#' https://doi.org/10.24432/C5DW2B.
#'
#' @references
#' Street, W. N., Wolberg, W. H., & Mangasarian, O. L. (1993, July). Nuclear
#' feature extraction for breast tumor diagnosis. In Biomedical image processing
#' and biomedical visualization (Vol. 1905, pp. 861-870). SPIE.
#'
#' @srrstats {G1.0} Reference section reports the related literature
#' @srrstats {G1.4} roxigen2 is used
#' @srrstats {G5.1} the data set is made available
#'
"breast_cancer"
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