tuning with outcome level "class"

[simonpcouch]

I came across this while writing tests for a fix to tidymodels/stacks#125. It seems like tuning fails when the level of an outcome is "class":

library(tidymodels)

# works okay with class_1 and class_2:
x <- tibble(
  class = sample(c("class_1", "class_2"), 100, replace = TRUE),
  a = rnorm(100),
  b = rnorm(100)
)

res <- tune_grid(
  logistic_reg(engine = 'glmnet', penalty = tune(), mixture = 1),
  preprocessor = recipe(class ~ ., x),
  resamples = vfold_cv(x, 2),
  grid = 2,
  control = control_grid()
)

# fails on outcome with level "class"
x_ <- tibble(
  class = sample(c("class_1", "class"), 100, replace = TRUE),
  a = rnorm(100),
  b = rnorm(100)
)

res_ <- tune_grid(
  logistic_reg(engine = 'glmnet', penalty = tune(), mixture = 1),
  preprocessor = recipe(class ~ ., x_),
  resamples = vfold_cv(x_, 2),
  grid = 2,
  control = control_grid()
)
#> x Fold1: internal: Error:
#> ! In metric: `accuracy`
#> Problem while computing `.estim...
#> x Fold2: internal: Error:
#> ! In metric: `accuracy`
#> Problem while computing `.estim...
#> Warning: All models failed. See the `.notes` column.

^{Created on 2022-05-03 by the reprex package (v2.0.1)}

[simonpcouch]

Closed in #720.

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