| mlr_measures {mlr3} | R Documentation |
Dictionary of Performance Measures
Description
A simple mlr3misc::Dictionary storing objects of class Measure.
Each measure has an associated help page, see mlr_measures_[id].
This dictionary can get populated with additional measures by add-on packages. E.g., mlr3proba adds survival measures and mlr3cluster adds cluster analysis measures.
For a more convenient way to retrieve and construct measures, see msr()/msrs().
Format
R6::R6Class object inheriting from mlr3misc::Dictionary.
Methods
See mlr3misc::Dictionary.
S3 methods
-
as.data.table(dict, ..., objects = FALSE)
mlr3misc::Dictionary ->data.table::data.table()
Returns adata.table::data.table()with fields "key", "label", "task_type", "packages", "predict_type", and "task_properties" as columns. Ifobjectsis set toTRUE, the constructed objects are returned in the list column namedobject.
See Also
Sugar functions: msr(), msrs()
Implementation of most measures: mlr3measures
Other Dictionary:
mlr_learners,
mlr_resamplings,
mlr_task_generators,
mlr_tasks
Other Measure:
Measure,
MeasureClassif,
MeasureRegr,
MeasureSimilarity,
mlr_measures_aic,
mlr_measures_bic,
mlr_measures_classif.costs,
mlr_measures_debug_classif,
mlr_measures_elapsed_time,
mlr_measures_internal_valid_score,
mlr_measures_oob_error,
mlr_measures_selected_features
Examples
as.data.table(mlr_measures)
mlr_measures$get("classif.ce")
msr("regr.mse")