mlr_measures_forecast.rmse: Root Mean Squared Error Measure

In mlr-org/mlr3forecasting: Forecasting for 'mlr3'

Root Mean Squared Error Measure

Description

Root Mean Squared Error Measure

Root Mean Squared Error Measure

Dictionary

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

mlr_measures$get("forecast.rmse")
msr("forecast.rmse")

Meta Information

• Task type: “forecast”

• Range: [0, \infty)

• Minimize: TRUE

• Average: macro

• Required Prediction: “response”

• Required Packages: mlr3, mlr3temporal

Parameters

Empty ParamSet

Super classes

mlr3::Measure -> mlr3temporal::MeasureForecast -> mlr3temporal::MeasureForecastRegr -> MeasureForecastRMSE

Methods

Public methods

• MeasureForecastRMSE$new()

• MeasureForecastRMSE$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

MeasureForecastRMSE$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureForecastRMSE$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/basics.html#train-predict

• 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: MeasureForecast, mlr_measures_forecast.mae, mlr_measures_forecast.mape, mlr_measures_forecast.mse, mlr_measures_forecast.regr

mlr-org/mlr3forecasting documentation built on June 29, 2023, 11:57 p.m.