library(bonsai)
#> Loading required package: parsnip

# This works with default mtry value
rf_mod <- 
  rand_forest() %>%
  set_engine(engine = "aorsf") %>%
  set_mode(mode = "regression") %>% 
  set_args(min_n = 1, trees = 2, importance = "permute") %>% 
  fit(
    formula = mpg  ~ . , 
    data = mtcars 
  )


rf_mod
#> parsnip model object
#> 
#> ---------- Oblique random regression forest
#> 
#>      Linear combinations: Accelerated Linear regression
#>           N observations: 32
#>                  N trees: 2
#>       N predictors total: 10
#>    N predictors per node: 4
#>  Average leaves per tree: 7.5
#> Min observations in leaf: 1
#>           OOB stat value: 0.27
#>            OOB stat type: RSQ
#>      Variable importance: permute
#> 
#> -----------------------------------------



# Error occurs...
rf_mod_w_mtry <- 
  rand_forest() %>%
  set_engine(engine = "aorsf") %>%
  set_mode(mode = "regression") %>% 
  set_args(mtry = 3, min_n = 1, trees = 2, importance = "permute") %>% 
  fit(
    formula = mpg  ~ . , 
    data = mtcars 
  )
#> Error in ncol(source): object "x" not found