mlr3 (version 0.2.0)

mlr_measures_elapsed_time: Elapsed Time Measure

Description

Measures the elapsed time during train ("time_train"), predict ("time_predict"), or both ("time_both").

Dictionary

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

mlr_measures$get("time_train")
msr("time_train")

Meta Information

• Type: NA

• Range: \([0, \infty)\)

• Minimize: TRUE

• Required prediction: 'response'

Super class

mlr3::Measure -> MeasureElapsedTime

Public fields

stages

(character()) Which stages of the learner to measure?

Methods

Public methods

• MeasureElapsedTime$new()

• MeasureElapsedTime$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

MeasureElapsedTime$new(id = "elapsed_time", stages)

Arguments

id

(character(1)) Identifier for the new instance.

stages

(character()) Subset of ("train", "predict"). The runtime of provided stages will be summed.

Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureElapsedTime$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_debug, mlr_measures_oob_error, mlr_measures_selected_features, mlr_measures