Calculates Sum of Squared Error in each cluster — sse_within • tidyclust

Calculates Sum of Squared Error in each cluster

Usage

sse_within(object, new_data = NULL, dist_fun = Rfast::dista)

Arguments

object: A fitted kmeans tidyclust model
new_data: A dataset to predict on. If NULL, uses trained clustering.
dist_fun: A function for calculating distances to centroids. Defaults to Euclidean distance on processed data.

Value

A tibble with two columns, the cluster name and the SSE within that cluster.

Details

sse_within_total() is the corresponding cluster metric function that returns the sum of the values given by sse_within().

Examples

kmeans_spec <- k_means(num_clusters = 5) %>%
  set_engine("stats")

kmeans_fit <- fit(kmeans_spec, ~., mtcars)

sse_within(kmeans_fit)
#> # A tibble: 5 × 3
#>   .cluster     wss n_members
#>   <fct>      <dbl>     <int>
#> 1 Cluster_1  7256.         6
#> 2 Cluster_2  3617.         7
#> 3 Cluster_3  6356.         6
#> 4 Cluster_4 46659.         9
#> 5 Cluster_5   208.         4