bonsai 0.2.1

• The most recent dials and parsnip releases introduced tuning integration for the lightgbm num_leaves engine argument! The num_leaves parameter sets the maximum number of nodes per tree, and is an important tuning parameter for lightgbm (tidymodels/dials#256, tidymodels/parsnip#838). With the newest version of each of dials, parsnip, and bonsai installed, tune this argument by marking the num_leaves engine argument for tuning when defining your model specification:

boost_tree() %>% set_engine("lightgbm", num_leaves = tune())

• Fixed a bug where lightgbm's parallelism argument num_threads was overridden when passed via param rather than as a main argument. By default, then, lightgbm will fit sequentially rather than with num_threads = foreach::getDoParWorkers(). The user can still set num_threads via engine arguments with engine = "lightgbm":

boost_tree() %>% set_engine("lightgbm", num_threads = x)

Note that, when tuning hyperparameters with the tune package, detection of parallel backend will still work as usual.

• The boost_tree argument stop_iter now maps to the lightgbm:::lgb.train() argument early_stopping_round rather than its alias early_stopping_rounds. This does not affect parsnip's interface to lightgbm (i.e. via boost_tree() %>% set_engine("lightgbm")), though will introduce errors for code that uses the train_lightgbm() wrapper directly and sets the lightgbm::lgb.train() argument early_stopping_round by its alias early_stopping_rounds via train_lightgbm()'s ....

• Disallowed passing main model arguments as engine arguments to set_engine("lightgbm", ...) via aliases. That is, if a main argument is marked for tuning and a lightgbm alias is supplied as an engine argument, bonsai will now error, rather than supplying both to lightgbm and allowing the package to handle aliases. Users can still interface with non-main boost_tree() arguments via their lightgbm aliases (#53).