hier_clust()
defines a model that fits clusters based on a distance-based
dendrogram
Usage
hier_clust(
mode = "partition",
engine = "stats",
num_clusters = NULL,
cut_height = NULL,
linkage_method = "complete"
)
Arguments
- mode
A single character string for the type of model. The only possible value for this model is "partition".
- engine
A single character string specifying what computational engine to use for fitting. Possible engines are listed below. The default for this model is
"stats"
.- num_clusters
Positive integer, number of clusters in model (optional).
- cut_height
Positive double, height at which to cut dendrogram to obtain cluster assignments (only used if
num_clusters
isNULL
)- linkage_method
the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of
"ward.D"
,"ward.D2"
,"single"
,"complete"
,"average"
(= UPGMA),"mcquitty"
(= WPGMA),"median"
(= WPGMC) or"centroid"
(= UPGMC).
Examples
# 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
#>