Skip to content

Latest commit

 

History

History
176 lines (99 loc) · 7.06 KB

NEWS.md

File metadata and controls

176 lines (99 loc) · 7.06 KB
Raw

textrecipes (development version)

  • Documentation for tidy methods for all steps has been improved to describe the return value more accurately. (#262)

  • Calling ?tidy.step_*() now sends you to the documentation for step_*() where the outcome is documented. (#261)

  • step_textfeatures() has been made faster and more robust. (#265)

  • Fixed bug in step_clean_levels() where it would produce NAs for character columns. (#274)

textrecipes 1.0.6

  • textfeatures has been removed from Suggests. (#255)

  • step_textfeatures() no longer returns a politeness feature. (#254)

textrecipes 1.0.5

  • step_untokenize() and step_normalization() now returns factors instead of strings. (#247)

textrecipes 1.0.4

Improvements

  • step_clean_names() now throw an informative error if needed non-standard role columns are missing during bake(). (#235)

  • The keep_original_cols argument has been added to step_tokenmerge. This change should mean that every step that produces new columns has the keep_original_cols argument. (#242)

  • Many internal changes to improve consistency and slight speed increases.

Bug Fixes

  • Fixed bug where step_dummy_hash() and step_texthash() would add new columns before old columns. (#235)

  • Fixed bug where vocabulary_size wasn't tunable in step_tokenize_bpe(). (#239)

textrecipes 1.0.3

Improvements

  • Steps with tunable arguments now have those arguments listed in the documentation.

  • All steps that add new columns will now informatively error if name collision occurs.

Bug Fixes

  • Fixed bug where step_tf() wasn't tunable for weight argument.

textrecipes 1.0.2

  • Setting token = "tweets" in step_tokenize() have been deprecated due to tokenizers::tokenize_tweets() being deprecated. (#209)

  • step_sequence_onehot(), step_dummy_hash(), step_dummy_texthash() now return integers. step_tf() returns integer when weight_scheme is "binary" or "raw count".

  • All steps now have required_pkgs() methods.

textrecipes 1.0.1

  • Examples no longer include if (require(...)) code.

textrecipes 1.0.0

  • Indicate which steps support case weights (none), to align documentation with other packages.

textrecipes 0.5.2

  • Remove use of okc_text in vignette

  • Fix bug in printing of tokenlists

textrecipes 0.5.1

  • step_tfidf() now correctly saves the idf values and applies them to the testing data set.

  • tidy.step_tfidf() now returns calculated IDF weights.

textrecipes 0.5.0

New steps

  • step_dummy_hash() generates binary indicators (possibly signed) from simple factor or character vectors.

  • step_tokenize() has gotten a couple of cousin functions step_tokenize_bpe(), step_tokenize_sentencepiece() and step_tokenize_wordpiece() which wraps {tokenizers.bpe}, {sentencepiece} and {wordpiece} respectively (#147).

Improvements and Other Changes

  • Added all_tokenized() and all_tokenized_predictors() to more easily select tokenized columns (#132).

  • Use show_tokens() to more easily debug a recipe involving tokenization.

  • Reorganize documentation for all recipe step tidy methods (#126).

  • Steps now have a dedicated subsection detailing what happens when tidy() is applied. (#163)

  • All recipe steps now officially support empty selections to be more aligned with dplyr and other packages that use tidyselect (#141).

  • step_ngram() has been given a speed increase to put it in line with other packages performance.

  • step_tokenize() will now try to error if vocabulary size is too low when using engine = "tokenizers.bpe" (#119).

  • Warning given by step_tokenfilter() when filtering failed to apply now correctly refers to the right argument name (#137).

  • step_tf() now returns 0 instead of NaN when there aren't any tokens present (#118).

  • step_tokenfilter() now has a new argument filter_fun will takes a function which can be used to filter tokens. (#164)

  • tidy.step_stem() now correctly shows if custom stemmer was used.

  • Added keep_original_cols argument to step_lda, step_texthash(), step_tf(), step_tfidf(), step_word_embeddings(), step_dummy_hash(), step_sequence_onehot(), and step_textfeatures() (#139).

Breaking Changes

  • Steps with prefix argument now creates names according to the pattern prefix_variablename_name/number. (#124)

textrecipes 0.4.1

Bug fixes

  • Fixed a bug in step_tokenfilter() and step_sequence_onehot() that sometimes caused crashes in R 4.1.0.

textrecipes 0.4.0

Breaking Changes

  • step_lda() now takes a tokenlist instead of a character variable. See readme for more detail.

New Features

  • step_sequence_onehot() now takes tokenlists as input.
  • added {tokenizers.bpe} engine to step_tokenize().
  • added {udpipe} engine to step_tokenize().
  • added new steps for cleaning variable names or levels with {janitor}, step_clean_names() and step_clean_levels(). (#101)

textrecipes 0.3.0

  • stopwords package have been moved from Imports to Suggests.
  • step_ngram() gained an argument min_num_tokens to be able to return multiple n-grams together. (#90)
  • Adds step_text_normalization() to perform unicode normalization on character vectors. (#86)

textrecipes 0.2.3

textrecipes 0.2.2

  • step_word_embeddings() got a argument aggregation_default to specify value in cases where no words matches embedding.

textrecipes 0.2.1

textrecipes 0.2.0

  • step_tokenize() got an engine argument to specify packages other then tokenizers to tokenize.
  • spacyr have been added as an engine to step_tokenize().
  • step_lemma() has been added to extract lemma attribute from tokenlists.
  • step_pos_filter() has been added to allow filtering of tokens bases on their pat of speech tags.
  • step_ngram() has been added to generate ngrams from tokenlists.
  • step_stem() not correctly uses the options argument. (Thanks to @grayskripko for finding bug, #64)

textrecipes 0.1.0

  • step_word2vec() have been changed to step_lda() to reflect what is actually happening.
  • step_word_embeddings() has been added. Allows for use of pre-trained word embeddings to convert token columns to vectors in a high-dimensional "meaning" space. (@jonthegeek, #20)
  • text2vec have been changed from Imports to Suggests.
  • textfeatures have been changed from Imports to Suggests.
  • step_tfidf() calculations are slightly changed due to flaw in original implementation dselivanov/text2vec#280.

textrecipes 0.0.2

  • Custom stemming function can now be used in step_stem using the custom_stemmer argument.
  • step_textfeatures() have been added, allows for multiple numerical features to be pulled from text.
  • step_sequence_onehot() have been added, allows for one hot encoding of sequences of fixed width.
  • step_word2vec() have been added, calculates word2vec dimensions.
  • step_tokenmerge() have been added, combines multiple list columns into one list-columns.
  • step_texthash() now correctly accepts signed argument.
  • Documentation have been improved to showcase the importance of filtering tokens before applying step_tf() and step_tfidf().

textrecipes 0.0.1

First CRAN version