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():
See also
Other survival measures:
mlr_measures_surv.calib_alpha
,
mlr_measures_surv.calib_beta
,
mlr_measures_surv.calib_index
,
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