textrecipes contain extra steps for the recipes
package for preprocessing text data.
You can install the released version of textrecipes from CRAN with:
Install the development version from GitHub with:
In the following example we will go through the steps needed, to convert a character variable to the TF-IDF of its tokenized words after removing stopwords, and, limiting ourself to only the 10 most used words. The preprocessing will be conducted on the variable medium
and artist
.
library(recipes)
library(textrecipes)
library(modeldata)
data("tate_text")
okc_rec <- recipe(~ medium + artist, data = tate_text) %>%
step_tokenize(medium, artist) %>%
step_stopwords(medium, artist) %>%
step_tokenfilter(medium, artist, max_tokens = 10) %>%
step_tfidf(medium, artist)
okc_obj <- okc_rec %>%
prep()
str(bake(okc_obj, tate_text))
#> tibble [4,284 × 20] (S3: tbl_df/tbl/data.frame)
#> $ tfidf_medium_colour : num [1:4284] 2.31 0 0 0 0 ...
#> $ tfidf_medium_etching : num [1:4284] 0 0.86 0.86 0.86 0 ...
#> $ tfidf_medium_gelatin : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_medium_lithograph : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_medium_paint : num [1:4284] 0 0 0 0 2.35 ...
#> $ tfidf_medium_paper : num [1:4284] 0 0.422 0.422 0.422 0 ...
#> $ tfidf_medium_photograph : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_medium_print : num [1:4284] 0 0 0 0 0 ...
#> $ tfidf_medium_screenprint: num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_medium_silver : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_akram : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_beuys : num [1:4284] 0 0 0 0 0 ...
#> $ tfidf_artist_ferrari : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_john : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_joseph : num [1:4284] 0 0 0 0 0 ...
#> $ tfidf_artist_león : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_richard : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_schütte : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_thomas : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
#> $ tfidf_artist_zaatari : num [1:4284] 0 0 0 0 0 0 0 0 0 0 ...
As of version 0.4.0, step_lda()
no longer accepts character variables and instead takes tokenlist variables.
the following recipe
can be replaced with the following recipe to achive the same results
lda_tokenizer <- function(x) text2vec::word_tokenizer(tolower(x))
recipe(~text_var, data = data) %>%
step_tokenize(text_var,
custom_token = lda_tokenizer
) %>%
step_lda(text_var)
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