mlr_sugar: Syntactic Sugar for Object Construction

mlr_sugarR Documentation

Syntactic Sugar for Object Construction


Functions to retrieve objects, set hyperparameters and assign to fields in one go. Relies on mlr3misc::dictionary_sugar_get() to extract objects from the respective mlr3misc::Dictionary:

  • tsk() for a Task from mlr_tasks.

  • tsks() for a list of Tasks from mlr_tasks.

  • tgen() for a TaskGenerator from mlr_task_generators.

  • tgens() for a list of TaskGenerators from mlr_task_generators.

  • lrn() for a Learner from mlr_learners.

  • lrns() for a list of Learners from mlr_learners.

  • rsmp() for a Resampling from mlr_resamplings.

  • rsmps() for a list of Resamplings from mlr_resamplings.

  • msr() for a Measure from mlr_measures.

  • msrs() for a list of Measures from mlr_measures.


tsk(.key, ...)

tsks(.keys, ...)

tgen(.key, ...)

tgens(.keys, ...)

lrn(.key, ...)

lrns(.keys, ...)

rsmp(.key, ...)

rsmps(.keys, ...)

msr(.key, ...)

msrs(.keys, ...)



Key passed to the respective dictionary to retrieve the object.


(named list())
Named arguments passed to the constructor, to be set as parameters in the paradox::ParamSet, or to be set as public field. See mlr3misc::dictionary_sugar_get() for more details.


Keys passed to the respective dictionary to retrieve multiple objects.


R6::R6Class object of the respective type, or a list of R6::R6Class objects for the plural versions.


# penguins task with new id
tsk("penguins", id = "penguins2")

# classification tree with different hyperparameters
# and predict type set to predict probabilities
lrn("classif.rpart", cp = 0.1, predict_type = "prob")

# multiple learners with predict type 'prob'
lrns(c("classif.featureless", "classif.rpart"), predict_type = "prob")

mlr3 documentation built on Nov. 2, 2022, 5:11 p.m.