save x column names from fit_xy()

[EmilHvitfeldt]

to close #1166.

This bug happened because we don't know the name of the outcome(s) y when using fit_xy() because it is often a nameless vector. So instead, what I tried to do was to save the names of the x and subset with those when appropriate.

This is NOT a xgboost issue. it is just that xgboost complains more loudly than other engines.

library(parsnip)

spec <- boost_tree() %>%
  set_mode("regression") %>%
  set_engine("xgboost")

lm_fit <- fit(spec, mpg ~ ., data = mtcars)

predict(lm_fit, mtcars)
#> # A tibble: 32 × 1
#>    .pred
#>    <dbl>
#>  1  20.9
#>  2  20.9
#>  3  22.6
#>  4  21.0
#>  5  18.4
#>  6  18.1
#>  7  14.2
#>  8  23.7
#>  9  22.4
#> 10  18.9
#> # ℹ 22 more rows

lm_fit <- fit_xy(spec, x = mtcars[, -1], y = mtcars[, 1])

predict(lm_fit, mtcars)
#> # A tibble: 32 × 1
#>    .pred
#>    <dbl>
#>  1  20.9
#>  2  20.9
#>  3  22.6
#>  4  21.0
#>  5  18.4
#>  6  18.1
#>  7  14.2
#>  8  23.7
#>  9  22.4
#> 10  18.9
#> # ℹ 22 more rows

^{Created on 2024-08-30 with reprex v2.1.0}

[simonpcouch]

Super clean!

My only question was whether there were any unexpected hiccups with non-standard roles, but all is well:

library(tidymodels)

data(biomass, package = "modeldata")
biomass_train <- biomass[1:100,]
biomass_test <- biomass[101:200,]

rec <- recipe(HHV ~ ., data = biomass_train) %>%
  update_role(sample, new_role = "id variable") %>%
  step_center(carbon) %>%
  step_dummy(all_nominal_predictors())

spec <- boost_tree() %>%
  set_mode("regression") %>%
  set_engine("xgboost")

wf <- fit(workflow(rec, spec), biomass_train)

predict(wf, biomass_train)
#> # A tibble: 100 × 1
#>    .pred
#>    <dbl>
#>  1  19.5
#>  2  19.2
#>  3  18.2
#>  4  17.9
#>  5  18.4
#>  6  18.4
#>  7  18.5
#>  8  18.2
#>  9  18.7
#> 10  18.8
#> # ℹ 90 more rows

^{Created on 2024-09-03 with reprex v2.1.1}

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