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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)This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
For questions and discussions about tidymodels packages, modeling, and machine learning, please post on RStudio Community.
If you think you have encountered a bug, please submit an issue.
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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