| sse_within_total | R Documentation | 
Compute the sum of within-cluster SSE
sse_within_total(object, ...)
## S3 method for class 'cluster_spec'
sse_within_total(object, ...)
## S3 method for class 'cluster_fit'
sse_within_total(object, new_data = NULL, dist_fun = NULL, ...)
## S3 method for class 'workflow'
sse_within_total(object, new_data = NULL, dist_fun = NULL, ...)
sse_within_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. | 
Not to be confused with sse_within() that returns a tibble
with within-cluster SSE, one row for each cluster.
A tibble with 3 columns; .metric, .estimator, and .estimate.
Other cluster metric: 
silhouette_avg(),
sse_ratio(),
sse_total()
kmeans_spec <- k_means(num_clusters = 5) |>
  set_engine("stats")
kmeans_fit <- fit(kmeans_spec, ~., mtcars)
sse_within_total(kmeans_fit)
sse_within_total_vec(kmeans_fit)
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