Validate sequence clusters descriptively

Usage

validate_sequence_clusters(clustering, distance = NULL)

Arguments

clustering: A result from cluster_sequences() or a named assignment vector.
distance: Optional distance object when clustering is an assignment vector.

Value

A list containing overall validation metrics, cluster sizes, and per-sequence silhouette values.

Examples

sequences <- data.frame(
  sequence_id = rep(c("s1", "s2", "s3", "s4"), each = 4L),
  sequence_order = rep(1:4, times = 4L),
  state = c("A", "B", "C", "D", "A", "B", "C", "C",
            "D", "C", "B", "A", "D", "C", "A", "A"),
  group = rep(c("g1", "g2"), each = 8L),
  stringsAsFactors = FALSE
)
distance <- compute_sequence_distance(sequences)
fit <- cluster_sequences(distance, k = 2L)
validate_sequence_clusters(fit)
#> $overall
#>   n_sequences n_clusters average_silhouette minimum_silhouette dunn_index
#> 1           4          2               0.75               0.75          4
#>   within_between_ratio singleton_clusters
#> 1                 0.25                  0
#> 
#> $cluster_sizes
#>   cluster size
#> 1       1    2
#> 2       2    2
#> 
#> $per_sequence
#>   sequence_id cluster silhouette
#> 1          s1       1       0.75
#> 2          s2       1       0.75
#> 3          s3       2       0.75
#> 4          s4       2       0.75
#>