fit_xy() usage for cross_validation in Tidy Models

There is not an x/y interface but an easy way to get there without a formula:

library(recipes)

rec <- recipe(mtcars)
summary(rec)
#> # A tibble: 11 x 4
#>    variable type    role  source  
#>    <chr>    <chr>   <lgl> <chr>   
#>  1 mpg      numeric NA    original
#>  2 cyl      numeric NA    original
#>  3 disp     numeric NA    original
#>  4 hp       numeric NA    original
#>  5 drat     numeric NA    original
#>  6 wt       numeric NA    original
#>  7 qsec     numeric NA    original
#>  8 vs       numeric NA    original
#>  9 am       numeric NA    original
#> 10 gear     numeric NA    original
#> 11 carb     numeric NA    original

# now add roles
rec <- 
  rec %>% 
  update_role(mpg, new_role = "outcome") %>% 
  update_role(-mpg, new_role = "predictor") 
summary(rec)
#> # A tibble: 11 x 4
#>    variable type    role      source  
#>    <chr>    <chr>   <chr>     <chr>   
#>  1 mpg      numeric outcome   original
#>  2 cyl      numeric predictor original
#>  3 disp     numeric predictor original
#>  4 hp       numeric predictor original
#>  5 drat     numeric predictor original
#>  6 wt       numeric predictor original
#>  7 qsec     numeric predictor original
#>  8 vs       numeric predictor original
#>  9 am       numeric predictor original
#> 10 gear     numeric predictor original
#> 11 carb     numeric predictor original

^{Created on 2020-11-06 by the reprex package (v0.3.0)}