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#' @rdname model_parameters.kmeans
#' @inheritParams cluster_centers
#'
#' @examples
#' \donttest{
#' # DBSCAN ---------------------------
#' if (require("dbscan", quietly = TRUE)) {
#' model <- dbscan::dbscan(iris[1:4], eps = 1.45, minPts = 10)
#'
#' rez <- model_parameters(model, iris[1:4])
#' rez
#'
#' # Get clusters
#' predict(rez)
#'
#' # Clusters centers in long form
#' attributes(rez)$means
#'
#' # Between and Total Sum of Squares
#' attributes(rez)$Sum_Squares_Total
#' attributes(rez)$Sum_Squares_Between
#'
#' # HDBSCAN
#' model <- dbscan::hdbscan(iris[1:4], minPts = 10)
#' model_parameters(model, iris[1:4])
#' }
#' }
#' @export
model_parameters.dbscan <- function(model, data = NULL, clusters = NULL, ...) {
if (is.null(data)) {
insight::format_error("This function requires the data used to compute the clustering to be provided via `data` as it is not accessible from the clustering object itself.")
}
if (is.null(clusters)) {
clusters <- model$cluster
}
params <- .cluster_centers_params(data, clusters, ...)
attr(params, "model") <- model
attr(params, "type") <- "dbscan"
attr(params, "title") <- ifelse(inherits(model, "hdbscan"), "HDBSCAN", "DBSCAN")
params
}
#' @export
model_parameters.hdbscan <- model_parameters.dbscan
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