mlr3 (version 0.5.0)

mlr_measures_debug: Debug Measure

Description

This measure returns the number of observations in the Prediction object. Its main purpose is debugging.

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

mlr_measures$get("debug")
msr("debug")

Meta Information

• Type: NA

• Range: \([0, \infty)\)

• Minimize: NA

• Required prediction: 'response'

Super class

mlr3::Measure -> MeasureDebug

Public fields

na_ratio

(numeric(1)) Ratio of scores which randomly should be NA, between 0 (default) and 1. Default is 0.

Methods

Public methods

• MeasureDebug$new()

• MeasureDebug$clone()

• mlr3::Measure$aggregate()

• mlr3::Measure$format()

• mlr3::Measure$help()

• mlr3::Measure$print()

• mlr3::Measure$score()

Method new()

Creates a new instance of this R6 class.

Usage

MeasureDebug$new()

Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureDebug$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Dictionary of Measures: mlr_measures

as.data.table(mlr_measures) for a complete table of all (also dynamically created) Measure implementations.

Other Measure: MeasureClassif, MeasureRegr, Measure, mlr_measures_classif.costs, mlr_measures_elapsed_time, mlr_measures_oob_error, mlr_measures_selected_features, mlr_measures

Examples

# NOT RUN {
task = tsk("wine")
learner = lrn("classif.featureless")
measure = msr("debug")
rr = resample(task, learner, rsmp("cv", folds = 3))
rr$score(measure)
# }