mlr_measures: Dictionary of Performance Measures

In mlr3: Machine Learning in R - Next Generation

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 a data.table::data.table() with fields "key", "label", "task_type", "packages", "predict_type", and "task_properties" as columns. If objects is set to TRUE, the constructed objects are returned in the list column named object.

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_regr.pinball, mlr_measures_regr.rqr, mlr_measures_regr.rsq, mlr_measures_selected_features

Examples

as.data.table(mlr_measures)
mlr_measures$get("classif.ce")
msr("regr.mse")

mlr3 documentation built on Sept. 14, 2025, 1:08 a.m.