Syntactic Sugar for Automatic Tuning

Source: R/sugar.R

Function to create an AutoTuner object.

auto_tuner(
  method,
  learner,
  resampling,
  measure,
  term_evals = NULL,
  term_time = NULL,
  search_space = NULL,
  ...
)

Arguments

method

(character(1))
Key to retrieve tuner from mlr_tuners dictionary.
learner

(mlr3::Learner).
resampling

(mlr3::Resampling)
Uninstantiated resamplings are instantiated during construction so that all configurations are evaluated on the same data splits.
measure

(mlr3::Measure)
Measure to optimize.
term_evals

(integer(1))
Number of allowed evaluations.
term_time

(integer(1))
Maximum allowed time in seconds.
search_space

(paradox::ParamSet).
...

(named list())
Named arguments to be set as parameters of the tuner.

Value

AutoTuner

Examples

learner = lrn("classif.rpart")
learner$param_set$values$minsplit = to_tune(1, 10)

at = auto_tuner(
  method = "random_search",
  learner = learner, 
  resampling = rsmp ("holdout"),
  measure = msr("classif.ce"), 
  term_evals = 50, 
  batch_size = 10)  

at$train(tsk("pima"))