dist.clust: Distance that incorporates weights from a clustering (hclust...
In tkonopka/MultiPattern: Multi-Pattern Discovery Framework

Distance that incorporates weights from a clustering (hclust or pam)

1 2	dist.clust(x, clust.dist = "euclidean", clust.method = "complete", clust.k = 2, clust.weight = 0.5, clust.alt = FALSE)

`x`	numeric matrix
`clust.dist`	character, determines what preliminary distance function is applied prior to clustering
`clust.method`	character, determines agglomeration method in hclust (e.g. complete, single, average) or "pam"
`clust.k`	integer, determines depth of clustering weights
`clust.weight`	numeric, determines weighting of cluster distances relative to neighbor rank distance. Set to 0 to obtain pure neighbor rank distance (clustering is ignored). Set to Inf to obtain pure cluster-based distance.
`clust.alt`	boolean. Set TRUE to obtain an alternative clustering. Default is FALSE which returns distances in which patterns from a usual distance are reinforced by clustering.