Mean Squared Error Measure

Mean Squared Error Measure

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.mse")
msr("forecast.mse")

Meta Information

• Task type: “forecast”

• Range: \([0, \infty)\)

• Minimize: TRUE

• Average: macro

• Required Prediction: “response”

• Required Packages: mlr3, mlr3temporal

Parameters

Empty ParamSet

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.regr, mlr_measures_forecast.rmse

Super classes

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

Methods

Public methods

• MeasureForecastMSE$new()

• MeasureForecastMSE$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

MeasureForecastMSE$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureForecastMSE$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.