Emil Hvitfeldt

Closing this as we already this this :)

closing in favor of https://github.com/tidymodels/recipes/issues/1158

I realize that some caution has to be taken for this step to work on applying the changes to the testing data set since it needs to retain the distribution...

Hello @trevorcampbell ! Thanks for the feature request, I don't know how this is normally done, so I'm gonna ask around and find out

Hello @katieburak 👋 Thank you for the bug report! I'll try to handle next time I get to do some tidyclust work

Hello @JauntyJJS 👋 That is a good idea, will be look into making that possible

This could be handled by setting letting `finalize_model()` be a generic. This way it is automatically handled in `finalize_workflow()`

Note: We have tidyclust specific function `finalize_workflow_tidyclust()`. This should either be referenced in the tune function or we move over to use refactor it ``` r library(tidymodels) library(tidyclust) #> #>...

Hello @tomazweiss 👋 thank you for this feature request, it seems reasonable. It feels like it would be an `augment()`-like operation. I need to think a little deeply to make...

I really don't want to violate the above listed prediction principles, so we might have to look into a different method to do "batch prediction".