Generate a clustering description plot from a rainette2 result

Generate a clustering description plot from a rainette2 result

Usage

rainette2_plot(
  res,
  dtm,
  k = NULL,
  criterion = c("chi2", "n"),
  complete_groups = FALSE,
  type = c("bar", "cloud"),
  n_terms = 15,
  free_scales = FALSE,
  measure = c("chi2", "lr", "frequency", "docprop"),
  show_negative = FALSE,
  text_size = 10
)

Arguments

res

result object of a rainette2 clustering

dtm

the dfm object used to compute the clustering

k

number of groups. If NULL, use the biggest number possible

criterion

criterion to use to choose the best partition. chi2 means the partition with the maximum sum of chi2, n the partition with the maximum size.

complete_groups

if TRUE, documents with NA cluster are reaffected by k-means clustering initialised with current groups centers.

type

type of term plots : barplot or wordcloud

n_terms

number of terms to display in keyness plots

free_scales

if TRUE, all the keyness plots will have the same scale

measure

statistics to compute

show_negative

if TRUE, show negative keyness features

text_size

font size for barplots, max word size for wordclouds

Value

A gtable object.

See also

quanteda.textstats::textstat_keyness(), rainette2_explor(), rainette2_complete_groups()