mlr_measures_surv.mse | R Documentation |
Calculates the mean squared error (MSE).
The MSE is defined by
1/n ∑ ((t - t*)^2)
where t is the true value and t* is the prediction.
Censored observations in the test set are ignored.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
MeasureSurvMSE$new() mlr_measures$get("surv.mse") msr("surv.mse")
Type: "surv"
Range: [0, Inf)
Minimize: TRUE
Required prediction: response
mlr3::Measure
-> mlr3proba::MeasureSurv
-> MeasureSurvMSE
new()
Creates a new instance of this R6 class.
MeasureSurvMSE$new()
clone()
The objects of this class are cloneable with this method.
MeasureSurvMSE$clone(deep = FALSE)
deep
Whether to make a deep clone.
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.nagelk_r2
,
mlr_measures_surv.oquigley_r2
,
mlr_measures_surv.rcll
,
mlr_measures_surv.rmse
,
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.rmse
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