Hierarchical (Agglomerative) ClusteringSource:
hier_clust() defines a model that fits clusters based on a distance-based
hier_clust( mode = "partition", engine = "stats", num_clusters = NULL, cut_height = NULL, linkage_method = "complete" )
A single character string for the type of model. The only possible value for this model is "partition".
A single character string specifying what computational engine to use for fitting. Possible engines are listed below. The default for this model is
Positive integer, number of clusters in model (optional).
Positive double, height at which to cut dendrogram to obtain cluster assignments (only used if
the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of
"median"(= WPGMC) or
# Show all engines modelenv::get_from_env("hier_clust") #> # A tibble: 1 × 2 #> engine mode #> <chr> <chr> #> 1 stats partition hier_clust() #> Hierarchical Clustering Specification (partition) #> #> Main Arguments: #> linkage_method = complete #> #> Computational engine: stats #>