#' @examples
#' # ---------------------------------------------------------------------------
#' # Multiclass example
#'
#' # `obs` is a 4 level factor. The first level is `"VF"`, which is the
#' # "event of interest" by default in yardstick. See the Relevant Level
#' # section above.
#' data(hpc_cv)
#'
#' # You can use the col1:colN tidyselect syntax
#' library(dplyr)
#' hpc_cv %>%
#' filter(Resample == "Fold01") %>%
#' <%=fn %>(obs, VF:L)
#'
#' # Change the first level of `obs` from `"VF"` to `"M"` to alter the
#' # event of interest. The class probability columns should be supplied
#' # in the same order as the levels.
#' hpc_cv %>%
#' filter(Resample == "Fold01") %>%
#' mutate(obs = relevel(obs, "M")) %>%
#' <%=fn %>(obs, M, VF:L)
#'
#' # Groups are respected
#' hpc_cv %>%
#' group_by(Resample) %>%
#' <%=fn %>(obs, VF:L)
#'
#' # Weighted macro averaging
#' hpc_cv %>%
#' group_by(Resample) %>%
#' <%=fn %>(obs, VF:L, estimator = "macro_weighted")
#'
#' # Vector version
#' # Supply a matrix of class probabilities
#' fold1 <- hpc_cv %>%
#' filter(Resample == "Fold01")
#'
#' <%=fn %>_vec(
#' truth = fold1$obs,
#' matrix(
#' c(fold1$VF, fold1$F, fold1$M, fold1$L),
#' ncol = 4
#' )
#' )
#'
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