R/LETTER.R

In evtclass: Extreme Value Theory for Open Set Classification - GPD and GEV Classifiers

#' Database of character image features.
#'
#' A dataset containing 16 features extracted from 20000 handwritten characters.
#'
#' @format A data frame with 20000 rows and 17 variables:
#' \describe{
#'   \item{class}{class labels}
#'   \item{V1}{first extracted feature}
#'   \item{V2}{second extracted feature}
#'   \item{V3}{third extracted feature}
#'   \item{V4}{4th extracted feature}
#'   \item{V5}{5th extracted feature}
#'   \item{V6}{6th extracted feature}
#'   \item{V7}{7th extracted feature}
#'   \item{V8}{8th extracted feature}
#'   \item{V9}{9th extracted feature}
#'   \item{V10}{10th extracted feature}
#'   \item{V11}{11th extracted feature}
#'   \item{V12}{12th extracted feature}
#'   \item{V13}{13th extracted feature}
#'   \item{V14}{14th extracted feature}
#'   \item{V15}{15th extracted feature}
#'   \item{V16}{16th extracted feature}
#' }
#' @source \url{https://archive.ics.uci.edu/ml/datasets/letter+recognition/}
"LETTER"