Changelog

Source: NEWS.md

embed 0.1.0 Unreleased

• 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.

embed 0.0.6 2020-03-17

• Small changes for base R’s stringsAsFactors change.

2020-01-07 embed 0.0.5

• The example data are now in the modeldata package.

• Small TF updates to step_embed().

2019-09-15 embed 0.0.4

• 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.

2019-07-12 embed 0.0.3

New Steps

• step_umap() was added for both supervised and unsupervised encodings.
• step_woe() created weight of evidence encodings.

2018-11-19 embed 0.0.2

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

2018-09-14 embed 0.0.1

First CRAN version