Determine Optimal Number of Clusters for Hierarchical Clustering

Use silhouette or gap statistic to find optimal k

Usage

optimal_hclust_k(hclust_obj, method = "silhouette", max_k = 10)

Arguments

hclust_obj

A tidy_hclust object

method

Character; "silhouette" (default) or "gap"

max_k

Maximum number of clusters to test (default: 10)

Value

A list containing:

• optimal_k: the recommended number of clusters

• method: the evaluation method used

• values: numeric vector of evaluation scores (for silhouette)

• k_range: integer vector of k values tested (for silhouette)

If method = "gap", returns a tidy_gap object instead.

Examples

# \donttest{
hc <- tidy_hclust(USArrests, method = "ward.D2")
opt <- optimal_hclust_k(hc, method = "silhouette", max_k = 6)
# }