boost_tree_C5.0.md
In parsnip: A Common API to Modeling and Analysis Functions

C5.0 execution

Code
  res <- fit(lc_basic, funded_amnt ~ term, data = lending_club, engine = "C5.0",
  control = ctrl)
Condition
  Error in `.convert_form_to_xy_fit()`:
  ! The argument `engine` cannot be used to create the data.
  Possible arguments are subset or weights.

submodel prediction

Code
  multi_predict(class_fit, newdata = wa_churn[1:4, vars], trees = 4, type = "prob")
Condition
  Error in `multi_predict()`:
  ! Please use `new_data` instead of `newdata`.

argument checks for data dimensions

Code
  f_fit <- spec %>% fit(species ~ ., data = penguins)
Condition
  Warning:
  ! 1000 samples were requested but there were 333 rows in the data.
  i 333 will be used.

Code
  xy_fit <- spec %>% fit_xy(x = penguins[, -1], y = penguins$species)
Condition
  Warning:
  ! 1000 samples were requested but there were 333 rows in the data.
  i 333 will be used.