lightgbm.md
In bonsai: Model Wrappers for Tree-Based Models

boost_tree with lightgbm

Code
  boost_tree() %>% set_engine("lightgbm") %>% set_mode("regression")
Output
  Boosted Tree Model Specification (regression)

  Computational engine: lightgbm

Code
  boost_tree() %>% set_engine("lightgbm", nrounds = 100) %>% set_mode(
    "classification")
Output
  Boosted Tree Model Specification (classification)

  Engine-Specific Arguments:
    nrounds = 100

  Computational engine: lightgbm

bonsai handles mtry vs mtry_prop gracefully

The supplied argument `mtry = 0.5` must be greater than or equal to 1.

`mtry` is currently being interpreted as a count rather than a proportion. Supply `counts = FALSE` to `set_engine` to supply this argument as a proportion rather than a count.

See `?train_lightgbm` for more details.

The supplied argument `mtry = 3` must be less than or equal to 1.

`mtry` is currently being interpreted as a proportion rather than a count. Supply `counts = TRUE` to `set_engine` to supply this argument as a count rather than a proportion.

See `?train_lightgbm` for more details.

Code
  pars_fit_8 <- boost_tree(mtry = 0.5) %>% set_engine("lightgbm",
    feature_fraction_bynode = 0.5) %>% set_mode("regression") %>% fit(
    bill_length_mm ~ ., data = penguins)
Warning <rlang_warning>
  The following arguments cannot be manually modified and were removed: feature_fraction_bynode.
Error <rlang_error>
  The supplied argument `mtry = 0.5` must be greater than or equal to 1.

  `mtry` is currently being interpreted as a count rather than a proportion. Supply `counts = FALSE` to `set_engine` to supply this argument as a proportion rather than a count.

  See `?train_lightgbm` for more details.

training wrapper warns on protected arguments

Code
  boost_tree() %>% set_engine("lightgbm", n_iter = 10) %>% set_mode("regression") %>%
    fit(bill_length_mm ~ ., data = penguins)
Error <rlang_error>
  ! The `n_iter` argument passed to `set_engine()` (`?parsnip::set_engine()`) is an alias for a main model argument.
  i Please instead pass this argument via the `trees` argument to `boost_tree()` (`?parsnip::boost_tree()`).

Code
  boost_tree() %>% set_engine("lightgbm", num_tree = 10) %>% set_mode(
    "regression") %>% fit(bill_length_mm ~ ., data = penguins)
Error <rlang_error>
  ! The `num_tree` argument passed to `set_engine()` (`?parsnip::set_engine()`) is an alias for a main model argument.
  i Please instead pass this argument via the `trees` argument to `boost_tree()` (`?parsnip::boost_tree()`).

Code
  boost_tree() %>% set_engine("lightgbm", min_split_gain = 2) %>% set_mode(
    "regression") %>% fit(bill_length_mm ~ ., data = penguins)
Error <rlang_error>
  ! The `min_split_gain` argument passed to `set_engine()` (`?parsnip::set_engine()`) is an alias for a main model argument.
  i Please instead pass this argument via the `loss_reduction` argument to `boost_tree()` (`?parsnip::boost_tree()`).

Code
  boost_tree() %>% set_engine("lightgbm", min_split_gain = 2, lambda_l2 = 0.5) %>%
    set_mode("regression") %>% fit(bill_length_mm ~ ., data = penguins)
Error <rlang_error>
  ! The `min_split_gain` argument passed to `set_engine()` (`?parsnip::set_engine()`) is an alias for a main model argument.
  i Please instead pass this argument via the `loss_reduction` argument to `boost_tree()` (`?parsnip::boost_tree()`).