mlr_measures_elapsed_time: Elapsed Time Measure

In mlr3: Machine Learning in R - Next Generation

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

• Task type: “NA”

• Range: [0, \infty)

• Minimize: TRUE

• Average: macro

• Required Prediction: “NA”

• Required Packages: mlr3

Parameters

Empty ParamSet

Super class

mlr3::Measure -> MeasureElapsedTime

Public fields

stages

(character())
Which stages of the learner to measure? Usually set during construction.

Methods

Public methods

• MeasureElapsedTime$new()

• MeasureElapsedTime$clone()

Inherited methods

• mlr3::Measure$aggregate()
• mlr3::Measure$format()
• mlr3::Measure$help()
• mlr3::Measure$print()
• mlr3::Measure$score()

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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

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter2/data_and_basic_modeling.html#sec-eval

• Package mlr3measures for the scoring functions. Dictionary of Measures: mlr_measures as.data.table(mlr_measures) for a table of available Measures in the running session (depending on the loaded packages).

• Extension packages for additional task types:

  • mlr3proba for probabilistic supervised regression and survival analysis.

  • mlr3cluster for unsupervised clustering.

Other Measure: MeasureClassif, MeasureRegr, MeasureSimilarity, Measure, mlr_measures_aic, mlr_measures_bic, mlr_measures_classif.costs, mlr_measures_debug_classif, mlr_measures_oob_error, mlr_measures_selected_features, mlr_measures

mlr3 documentation built on Nov. 17, 2023, 5:07 p.m.