Nothing
new_ml_model_bisecting_kmeans <- function(pipeline_model, formula, dataset,
features_col) {
m <- new_ml_model_clustering(
pipeline_model = pipeline_model,
formula = formula,
dataset = dataset,
features_col = features_col,
class = "ml_model_bisecting_kmeans"
)
model <- m$model
m$summary <- model$summary
m$centers <- model$cluster_centers() %>%
do.call(rbind, .) %>%
as.data.frame() %>%
rlang::set_names(m$feature_names)
m$cost <- suppressWarnings(
possibly_null(
~ pipeline_model %>%
ml_stage(1) %>%
ml_transform(dataset) %>%
model$compute_cost()
)()
)
m
}
#' @export
print.ml_model_bisecting_kmeans <- function(x, ...) {
preamble <- sprintf(
"K-means clustering with %s %s",
nrow(x$centers),
if (nrow(x$centers) == 1) "cluster" else "clusters"
)
cat(preamble, sep = "\n")
print_newline()
ml_model_print_centers(x)
print_newline()
cat(
"Within Set Sum of Squared Errors = ",
if (is.null(x$cost)) "not computed." else x$cost
)
}
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