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#' Fine foods example data
#'
#' @details
#' These data are from Amazon, who describe it as "This dataset consists of
#' reviews of fine foods from amazon. The data span a period of more than 10
#' years, including all ~500,000 reviews up to October 2012. Reviews include
#' product and user information, ratings, and a plaintext review."
#'
#' A subset of the data are contained here and are split into a training and
#' test set. The training set sampled 10 products and retained all of their
#' individual reviews. Since the reviews within these products are correlated,
#' we recommend resampling the data using a leave-one-product-out approach. The
#' test set sampled 500 products that were not included in the training set
#' and selected a single review at random for each.
#'
#' There is a column for the product, a column for the text of the review, and
#' a factor column for a class variable. The outcome is whether the reviewer
#' gave the product a 5-star rating or not.
#'
#' @name small_fine_foods
#' @aliases small_fine_foods training_data testing_data
#' @docType data
#' @return \item{training_data,testing_data}{tibbles}
#'
#' @source https://snap.stanford.edu/data/web-FineFoods.html
#'
#'
#' @keywords datasets
#' @examples
#' data(small_fine_foods)
#' str(training_data)
#' str(testing_data)
NULL
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