Release tidypredict 1.0.0 · tidymodels/tidypredict

Breaking Changes

Random forest implementations (ranger and randomForest) will now produce a single formula instead of a list of expressions. (#84)

xgboost models with objectives "reg:tweedie" and "count:poisson" are now supported. (#72, @SimonCoulombe)
tree based models now uses .default argument in produced case_when() code when applicable. (#153)
Speed up tidypredict_fit() for partykit and ranger packages. (#125)
Speed up tidypredict_fit() for xgboost models. (#130)
randomForest models now support regression outcomes. (#77)
An informative error will now be thrown if a lm model cannot be processed due to having linear combinations of predictors. (#124)
linear models such as lm() and glm() now work with interactions created with * and :. (#74)
Cubist rules will return simplified rules whenever possible to avoid multiplying by 0 and 1. (#152)
Make work with xgboost version > 2.0.0.0. (#169)

Fixed a bug where the intercept was added incorrectly to the result for cubist models. (#58)
Fixed bug where tidypredict would error on Cubist models without conditions. (#127)
Fixed bug where Cubst models incorrectly combined rules and committees. (#134)