Skip to contents

Root Mean Squared Error Survival Measure

Source: R/MeasureSurvRMSE.R
mlr_measures_surv.rmse.Rd

Calculates the root mean squared error (RMSE).

The RMSE is defined by $$\sqrt{\frac{1}{n} \sum ((t - \hat{t})^2)}$$ where \(t\) is the true value and \(\hat{t}\) is the prediction.

Censored observations in the test set are ignored.

Dictionary

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

MeasureSurvRMSE$new()
mlr_measures$get("surv.rmse")
msr("surv.rmse")

Parameters

IdTypeDefaultLevels
selogicalFALSETRUE, FALSE

Meta Information

  • Type: "surv"

  • Range: \([0, \infty)\)

  • Minimize: TRUE

  • Required prediction: response

Parameter details

  • se (logical(1))
    If TRUE then returns standard error of the measure otherwise returns the mean across all individual scores, e.g. the mean of the per observation scores. Default is FALSE (returns the mean).

See also

Other survival measures: mlr_measures_surv.calib_alpha, mlr_measures_surv.calib_beta, mlr_measures_surv.chambless_auc, mlr_measures_surv.cindex, mlr_measures_surv.dcalib, mlr_measures_surv.graf, mlr_measures_surv.hung_auc, mlr_measures_surv.intlogloss, mlr_measures_surv.logloss, mlr_measures_surv.mae, mlr_measures_surv.mse, mlr_measures_surv.nagelk_r2, mlr_measures_surv.oquigley_r2, mlr_measures_surv.rcll, mlr_measures_surv.schmid, mlr_measures_surv.song_auc, mlr_measures_surv.song_tnr, mlr_measures_surv.song_tpr, mlr_measures_surv.uno_auc, mlr_measures_surv.uno_tnr, mlr_measures_surv.uno_tpr, mlr_measures_surv.xu_r2

Other response survival measures: mlr_measures_surv.mae, mlr_measures_surv.mse

Super classes

mlr3::Measure -> mlr3proba::MeasureSurv -> MeasureSurvRMSE

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

MeasureSurvRMSE$new()

Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureSurvRMSE$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.