Create an array of resampled dfms.
bootstrap_dfm(x, n = 10, ..., verbose = quanteda_options("verbose"))A named list of dfm objects, where the first, dfm_0, is
the dfm from the original texts, and subsequent elements are the
sentence-resampled dfms.
Function produces multiple, resampled dfm objects, based on resampling sentences (with replacement) from each document, recombining these into new "documents" and computing a dfm for each. Resampling of sentences is done strictly within document, so that every resampled document will contain at least some of its original tokens.
set.seed(10)
txt <- c(textone = "This is a sentence. Another sentence. Yet another.",
texttwo = "Premiere phrase. Deuxieme phrase.")
dfmat <- corpus_reshape(corpus(txt), to = "sentences") |>
tokens() |>
dfm()
bootstrap_dfm(dfmat, n = 3)
#>
#> $dfm_0
#> Document-feature matrix of: 2 documents, 10 features (45.00% sparse) and 0 docvars.
#> features
#> docs this is a sentence . another yet premiere phrase deuxieme
#> textone 1 1 1 2 3 2 1 0 0 0
#> texttwo 0 0 0 0 2 0 0 1 2 1
#>
#> $dfm_1
#> Document-feature matrix of: 2 documents, 10 features (50.00% sparse) and 0 docvars.
#> features
#> docs this is a sentence . another yet premiere phrase deuxieme
#> textone 1 1 1 2 3 2 1 0 0 0
#> texttwo 0 0 0 0 2 0 0 0 2 2
#>
#> $dfm_2
#> Document-feature matrix of: 2 documents, 10 features (65.00% sparse) and 0 docvars.
#> features
#> docs this is a sentence . another yet premiere phrase deuxieme
#> textone 0 0 0 1 3 3 2 0 0 0
#> texttwo 0 0 0 0 2 0 0 2 2 0
#>
#> $dfm_3
#> Document-feature matrix of: 2 documents, 10 features (60.00% sparse) and 0 docvars.
#> features
#> docs this is a sentence . another yet premiere phrase deuxieme
#> textone 0 0 0 1 3 3 2 0 0 0
#> texttwo 0 0 0 0 2 0 0 1 2 1
#>
#> attr(,"class")
#> [1] "dfm_bootstrap"