[Experimental] Compute document/feature proximity

This is an underlying function for textstat_dist and textstat_simil but returns TsparseMatrix.

textstat_proxy(x, selection = NULL, margin = c("documents",
  "features"), method = c("cosine", "correlation", "jaccard", "ejaccard",
  "dice", "edice", "hamman", "simple matching", "faith", "euclidean",
  "chisquared", "hamming", "kullback", "manhattan", "maximum", "canberra",
  "minkowski"), p = 2, min_proxy = NULL, rank = NULL)

Arguments

x	a dfm object
selection	a valid index for document or feature names (depending on margin) from x, to be selected for comparison
margin	identifies the margin of the dfm on which similarity or difference will be computed: "documents" for documents or "features" for word/term features.
method	method the similarity or distance measure to be used; see Details.
p	The power of the Minkowski distance.
min_proxy	the minimum proximity value to be recoded.
rank	an integer value specifying top-n most proximity values to be recorded.

See also

textstat_dist, textstat_simil