Summary Method for net_clustering
Usage
# S3 method for class 'net_clustering'
summary(object, ...)Examples
seqs <- data.frame(V1 = c("A","B","C","A","B"), V2 = c("B","C","A","B","A"),
V3 = c("C","A","B","C","B"))
cl <- build_clusters(seqs, k = 2)
summary(cl)
#> Sequence Clustering Summary
#> Method: pam
#> Dissimilarity: hamming
#> Silhouette: 0.6
#>
#> Per-cluster statistics:
#> cluster size mean_within_dist
#> 1 2 0
#> 2 3 2
#> cluster size mean_within_dist
#> 1 1 2 0
#> 2 2 3 2
# \donttest{
set.seed(1)
seqs <- data.frame(
V1 = sample(c("A","B","C"), 20, TRUE),
V2 = sample(c("A","B","C"), 20, TRUE),
V3 = sample(c("A","B","C"), 20, TRUE)
)
cl <- build_clusters(seqs, k = 2)
summary(cl)
#> Sequence Clustering Summary
#> Method: pam
#> Dissimilarity: hamming
#> Silhouette: 0.3407
#>
#> Per-cluster statistics:
#> cluster size mean_within_dist
#> 1 11 1.600000
#> 2 9 1.444444
#> cluster size mean_within_dist
#> 1 1 11 1.600000
#> 2 2 9 1.444444
# }