# https://github.com/tidymodels/parsnip/blob/main/R/augment.R
#' Augment data with predictions
#'
#' `augment()` will add column(s) for predictions to the given data.
#'
#' For partition models, a `.pred_cluster` column is added.
#'
#' @param x A [`cluster_fit`] object produced by [fit.cluster_spec()] or
#' [fit_xy.cluster_spec()] .
#' @param new_data A data frame or matrix.
#' @param ... Not currently used.
#' @rdname augment
#' @return A `tibble::tibble()` with containing `new_data` with columns added
#' depending on the mode of the model.
#' @examples
#' kmeans_spec <- k_means(num_clusters = 5) %>%
#' set_engine("stats")
#'
#' kmeans_fit <- fit(kmeans_spec, ~., mtcars)
#'
#' kmeans_fit %>%
#' augment(new_data = mtcars)
#' @export
augment.cluster_fit <- function(x, new_data, ...) {
ret <- new_data
if (x$spec$mode == "partition") {
check_spec_pred_type(x, "cluster")
ret <- dplyr::bind_cols(
ret,
stats::predict(x, new_data = new_data)
)
} else {
cli::cli_abort("Unknown mode: {x$spec$mode}")
}
as_tibble(ret)
}
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