Changes in version 1.2.2.9000 Changes in version 1.2.2 (2026-01-29) - Fixed bug on step_umap() where the number of calculated components would be zero. (#271) Changes in version 1.2.1 (2025-12-01) Improvements - Make work with all versions of xgboost. (#267) Changes in version 1.2.0 (2025-09-08) Improvements - Adds step_lencode() to perform analytical likelihood encoding. (#258) - Adds smooth argument to step_lencode() to allow for partial pooling in numeric outcomes. (#261) - step_feature_hash() has been fully deprecated in favor of textrecipes::step_dummy_hash(). (#253) Changes in version 1.1.5 (2025-01-22) Improvements - step_umap() has tunable initial and target_weight arguments. (#223, #222) - All messages, warnings and errors has been translated to use {cli} package (#153, #155). Changes in version 1.1.4 (2024-03-20) Improvements - step_umap() has gained initial and target_weight arguments. (#213) - Calling ?tidy.step_*() now sends you to the documentation for step_*() where the outcome is documented. (#216) - Documentation for tidy methods for all steps has been improved to describe the return value more accurately. (#217) - {keras} and {tensorflow} have been moved to Suggests instead of Imports. (#218) Changes in version 1.1.3 (2023-10-28) - step_collapse_stringdist() will now return predictors as factors. (#204) - Fixed regression from 1.1.2 in step_lencode_glm() where it couldn't be used on multiple columns. Changes in version 1.1.2 (2023-08-17) Improvements - The keep_original_cols argument has been added to step_woe(). This change should mean that every step that produces new columns has the keep_original_cols argument. (#194) - Many internal changes to improve consistency and slight speed increases. Breaking Changes - step_pca_sparse(), step_pca_truncated() and step_pca_sparse_bayes() now returns data unaltered if num_comp = 0. This is done to be consistent with recipes steps of the same nature. (#190) Changes in version 1.1.1 (2023-05-30) Bug Fixes - Fixed bug where step_pca_truncated() didn't work with zero selection. (#181) - The tidy() methods for step_discretize_cart(), step_discretize_xgb(), step_embed(), step_feature_hash(), step_lencode_bayes(), step_lencode_glm(), step_lencode_mixed(), step_pca_sparse(), step_pca_sparse_bayes(), step_pca_truncated(), step_umap(), and step_woe() now correctly return zero-row tibbles when used with empty selections. (#181) Changes in version 1.1.0 (2023-04-14) New Steps - step_pca_truncated() has been added. This step only calculates the components that are required, and will be a speedup in cases where it is used on many variables. (#82) Improvements - step_collapse_stringdist() has gained method and options arguments to allow for different types of string distance calculations. (#152) - step_umap() has gained the argument metric. (#154) - step_embed() has gained the keep_original_cols argument. (#176) - All steps now have required_pkgs() methods. - 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. Changes in version 1.0.0 (2022-07-02) - step_collapse_cart() can pool a predictor's factor levels using a tree-based method. - step_collapse_stringdist() can pool a predictor's factor levels using string distances. - Case weights support have been added to step_discretize_cart(), step_discretize_xgb(), step_lencode_bayes(), step_lencode_glm(), and step_lencode_mixed(). Changes in version 0.2.0 (2022-04-13) - step_embed() now correctly defaults to have a random id with the word "embed". (#102) - step_feature_hash() is soft deprecated in embed in favor of step_dummy_hash() in textrecipes. (#95) - Steps now have a dedicated subsection detailing what happens when tidy() is applied. (#105) - Reorganize documentation for all recipe step tidy methods (#115). - Fixed a bug where woe_table() and step_woe() didn't respect the factor levels of the outcome. (109) Changes in version 0.1.5 (2021-11-24) - Re-licensed package from GPL-2 to MIT. See consent from copyright holders here. - The tunable parameter ranges for step_umap() were changed for neighbors, num_comp, and min_dist to prevent uwot segmentation faults. The step also check to see if the data dimensions are consistent with the argument values. - Two new PCA steps were added, each using sparse techniques for estimation: step_pca_sparse() and step_pca_sparse_bayes(). - Updated to use recipes_eval_select() from recipes 0.1.17 (#85). - Added prefix argument to step_umap() to harmonize with other recipes steps (#93). - All embed recipe steps now officially support empty selections to be more aligned with recipes, dplyr and other packages that use tidyselect. - step_woe() no longer warns about high-cardinality predictors when the recipe is estimated. Instead it warns when categories have fewer than 10 data points in the training set. (#74) Changes in version 0.1.4 (2021-01-16) - Minor release with changes to test for cases when CRAN cannot get xgboost to work on their Solaris configuration. - lme4 and rstanarm are now in the Suggests list so they are not automatically installed with embed. A message is written to the console if those packages are missing and their associated steps functions are invoked. Changes in version 0.1.3 (2020-11-12) - More changes to enable better parallel processing on windows. Changes in version 0.1.2 (2020-10-17) - Changes to enable better parallel processing on windows. Changes in version 0.1.1 (2020-07-03) - Changes to tests to get out of archive jail. - Updated the plumbing behind step_woe(). - Due to a bug in tensorflow, added a "warm start" to instigate a TF session if one does not currently exist. Changes in version 0.1.0 (2020-05-25) - Changes for dplyr 1.0.0 New Steps - step_discretize_xgb() and step_discretize_cart() can be used to convert numeric predictors to categorical using supervised binning methods based on tree models. Thanks to Konrad Semsch for the contribution. - Added step_feature_hash() for creating dummy variables using feature hashing. Breaking Changes - tidy.step_woe() now has column names consistent with other recipe steps. Bug fixes - Fixed a bug in detecting the TF version. Changes in version 0.0.6 (2020-03-17) - Small changes for base R's stringsAsFactors change. Changes in version 0.0.5 (2020-01-07) - The example data are now in the modeldata package. - Small TF updates to step_embed(). Changes in version 0.0.4 (2019-09-15) - Methods were added for a future generic called tunable(). This outlines which parameters in a step can/could be tuned. - Small updates to work with different versions of tidyr. Changes in version 0.0.3 (2019-07-12) New Steps - step_umap() was added for both supervised and unsupervised encodings. - step_woe() created weight of evidence encodings. Changes in version 0.0.2 (2018-11-19) A mostly maintainence release to be compatible with version 0.1.3 of recipes. Other Changes: - The package now depends on the generics pacakge to get the broom tidy methods. - Karim Lahrichi added the ability to use callbacks when fitting tensorflow models. PR Changes in version 0.0.1 (2018-09-14) First CRAN version