Root Mean Squared Error Survival Measure

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")

Meta Information

• Type: "surv"

• Range: \([0, \infty)\)

• Minimize: TRUE

• Required prediction: response

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.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

Active bindings

se

(logical(1))
If TRUE returns the standard error of the measure.

Methods

Public methods

• MeasureSurvRMSE$new()

• MeasureSurvRMSE$clone()

Inherited methods

• mlr3::Measure$aggregate()

• mlr3::Measure$format()

• mlr3::Measure$help()

• mlr3::Measure$score()

• mlr3proba::MeasureSurv$print()

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Method new()

Creates a new instance of this R6 class.

Usage

MeasureSurvRMSE$new(se = FALSE)

Arguments

se

(logical(1))
If TRUE returns the standard error of the measure.

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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.