| sse_total | R Documentation | 
Compute the total sum of squares
sse_total(object, ...)
## S3 method for class 'cluster_spec'
sse_total(object, ...)
## S3 method for class 'cluster_fit'
sse_total(object, new_data = NULL, dist_fun = NULL, ...)
## S3 method for class 'workflow'
sse_total(object, new_data = NULL, dist_fun = NULL, ...)
sse_total_vec(
  object,
  new_data = NULL,
  dist_fun = function(x, y) {
     philentropy::dist_many_many(x, y, method =
    "euclidean")
 },
  ...
)
object | 
 A fitted kmeans tidyclust model  | 
... | 
 Other arguments passed to methods.  | 
new_data | 
 A dataset to predict on.  If   | 
dist_fun | 
 A function for calculating distances to centroids. Defaults to Euclidean distance on processed data.  | 
A tibble with 3 columns; .metric, .estimator, and .estimate.
Other cluster metric: 
silhouette_avg(),
sse_ratio(),
sse_within_total()
kmeans_spec <- k_means(num_clusters = 5) |>
  set_engine("stats")
kmeans_fit <- fit(kmeans_spec, ~., mtcars)
sse_total(kmeans_fit)
sse_total_vec(kmeans_fit)
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