load_libs() with engine == "kknn" and factor predictors

[simonpcouch]

Closes #264. :) Same story as in #913.

library(parsnip)

mtcars$am <- as.factor(mtcars$am)
mtcars$cyl <- as.factor(mtcars$cyl)

nearest_neighbor() %>%  
  set_mode("classification") %>%
  set_engine("kknn") %>%
  fit(am ~ ., data = mtcars)
#> parsnip model object
#> 
#> 
#> Call:
#> kknn::train.kknn(formula = am ~ ., data = data, ks = min_rows(5,     data, 5))
#> 
#> Type of response variable: nominal
#> Minimal misclassification: 0.09375
#> Best kernel: optimal
#> Best k: 5

^{Created on 2023-03-09 with reprex v2.0.2}

[EmilHvitfeldt]

Amazing!

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