as.dfm()methods for tm
predict.textmodel_wordscores()now includes an
include_reftextsargument to exclude training texts from the predicted model object (#1229). The default behaviour is
include_reftexts = TRUE, producing the same behaviour as existed before the introduction of this argument. This allows rescaling based on the reference documents (since rescaling requires prediction on the reference documents) but provides an easy way to exclude the reference documents from the predicted quantities.
textplot_wordcloud()now uses code entirely internal to quanteda, instead of using the wordcloud package.
textplot_scale1d()by adjusting the refscores for
dfm_weight()for previously weighted dfm objects and when supplied thresholds are proportions instead of counts. (#1237)
summary.corpus(x, n = 101)when
ndoc(x) > 100(#1242).
predict.textmodel_wordscores(x, rescaling = "mv")that always reset the reference values for rescaling to the first and second documents (#1251).
textplot_keyness()are now resolved (#1233, #1233).