Seed labels from a clustering, for spreading or training

Turns an unsupervised partition into the labeled examples that hg_classify(), hg_neural() and hg_hypergat() take: from each cluster, the n nodes with the highest stationary probability pi (the cluster's most representative members under the random walk). Ties are broken alphabetically by node name so the selection is deterministic.

Usage

hg_seeds(embedding, n = 5L)

Arguments

embedding

The data.frame from hg_cluster(what = "embedding") – columns node, cluster, pi.

n

Seeds per cluster (default 5L); clusters smaller than n contribute all their nodes.

Value

A named character vector – names are node identifiers, values their cluster labels – ready to pass as the labels argument of hg_classify(), hg_neural() or hg_hypergat().

Examples

hg <- text_hypergraph(c(
  cooking_1 = "simmer the soup with onions and carrots",
  cooking_2 = "this soup recipe needs salt on a cold night",
  space_1 = "the telescope revealed a distant galaxy and stars",
  space_2 = "astronomers aimed the telescope at the stars all night"
), stop_words = c("the", "with", "and", "a", "this", "at", "on", "all"))
pool <- hg_cluster(hg, k = 2, seed = 1, what = "embedding")
hg_seeds(pool, n = 1)
#>   cooking_2     space_1 
#> "Cluster 1" "Cluster 2"