Ways to illustrate decision tree with tidymodels.

[Husada_x_Hertzsprung]

Greetings.

So far, what I know is this: I can use extract fit parsnip engine and summary to present the rules from a decision tree model in tidymodels framework.

What I want to know is, is there a way to visualize the rules in better prettier ways? Like if? Can we integrate outside package to visualize decision tree with the summary from tidymodels extracted parsnip engine output?

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I used C5 engine, and I found Plot a decision tree — plot.C5.0 • C50.
So I tried:

c5_obj_final <- whole_fit %>% 
  extract_fit_engine()

plot(c5_obj_final)

But it gave me an error:

Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : 
cannot coerce class ‘c("gg", "ggplot")’ to a data.frame

[Husada_x_Hertzsprung]

I found r - How to plot a tree produced by C5.0 in tidymodels? - Stack Overflow
and I tried that but got an error:

Error in `check_training_set()`:
! To prep new steps after prepping the original recipe, `retain = TRUE` must be set each time that the recipe is trained.

Then I added retain = TRUE in the prep() but it still gives out the same error.