#' Time series data set
#'
#' A dataset containing 56 times series z-normalized. Time series length is 286.
#' @docType data
#' @keywords datasets
#' @name coffee
#' @usage data(coffee)
#' @format A data frame with 56 rows and 287 variables including the class.
#' @source \url{https://www.cs.ucr.edu/%7Eeamonn/time_series_data_2018/}
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#' Wine recognition data
#'
#' This dataset is the result of a chemical analysis of wine grown in the same
#' region in Italy but derived from three different cultivars. The analysis determined
#' the quantities of 13 constituents found in each of the three types of wines.
#'
#' The dataset is taken from the UCI data repository, to which it was donated
#' by Riccardo Leardi, University of Genova. The attributes are as follows:
#' \itemize{
#' \item Alcohol
#' \item Malic acid
#' \item Ash
#' \item Alcalinity of ash
#' \item Magnesium
#' \item Total phenols
#' \item Flavanoids
#' \item Nonflavanoid phenols
#' \item Proanthocyanins
#' \item Color intensity
#' \item Hue
#' \item OD280/OD315 of diluted wines
#' \item Proline
#' \item Wine (class)
#' }
#' @docType data
#' @keywords datasets
#' @name wine
#' @usage data(wine)
#' @format A data frame with 178 rows and 14 variables including the class.
#' @source \url{https://archive.ics.uci.edu/ml/datasets/Wine}
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