CVL: Cross validation Loss for hierarchical clustering methods
In Monoxido45/PhyloHclust: What the Package Does (One Line, Title Case)

CVL	R Documentation

Cross validation Loss for hierarchical clustering methods

Leave one feature out Cross validation loss for comparing a list of hierarchical clustering methods.

CVL(
  data,
  cl.list,
  dists = "euclidean",
  mixed_dist = "gower",
  seed = 99,
  ncores = 2,
  median = FALSE
)

`data`	Data frame used to build hierarchical clustering
`cl.list`	Named list of hierarchical clustering methods: each entry is composed by the name of the hierarchical clustering algorithm (e.g. hclust) followed by a character vector of all it's underlying agglomeration methods selected for comparison (e.g. "complete", "ward.D2").
`dists`	Chosen distance (or list of distances) to compute dissimilarity matrix for each hierarchical clustering method. Default is "euclidean".
`mixed_dist`	Chosen mixed distance (or list of mixed distances) to compute dissimilarity matrix for each hierarchical clustering method. Mixed distances are preferable to use when there are categorical features present in the dataset. Default is "gower".
`seed`	Fixed random seed for SIMMAP algorithm. Default is 99.
`ncores`	Number of cores to parallelize the computing process. Default is 2.
`median`	Set whether to compute the median of the leave one feature out loss associated to every feature (TRUE) or the mean (FALSE). Default is FALSE.