tidypredict Unreleased

  • Adds support for categorical predictors in partykit

tidypredict 0.4.2 2019-07-15

  • Simplifies tests that verify ranger

  • Adds fit method for parsed xgboost models

  • Sets conditional requirement for xgboost, for test and vignette

tidypredict 0.4.0 2019-07-12

New features

  • Parses ranger classification models.

  • Adds method support for broom’s tidy() function. Regression models only

  • Adds as_parsed_model() function. It adds the proper class components to the list.

  • Adds initial support for partykit’s ctree() model

  • Adds support for parsnip fitted models: lm, randomForest, ranger, and earth

  • Adds support for xgb.Booster models provided by the xgboost package (@Athospd, #43)

  • Adds support for Cubist::cubist() models (# 36)

tidypredict 0.3.0 2019-01-10

New features

  • Adds support for MARS models provided by the earth package


  • New parsed models are now list objects as opposed to data frames.

  • tidypredict_to_column() no longer supports ranger and randomForest because of the multiple queries generated by multiple trees.

  • All functions that read the parsed models and create the tidy eval formula now use the list object.

  • Most of the code that depends on dplyr programming has been removed.

  • Removes dependencies on: tidyr, tibble

  • The x/y interface for earth models can now be used.

Bug Fixes

  • It now returns all of the trees instead of just one for tree based models (randomForest & ranger) (#29)

tidypredict 0.2.1 2018-12-20

Bug Fixes

  • tibble 2.0.0 compatibility fix (@krlmlr)

tidypredict 0.2.0 2018-02-25

New features

  • Add support for ranger() models.

Bug fixes

  • Using x ~. in a randomForest() formula fails (#18 @washcycle).