R: Mean Squared Error Survival Measure

mlr_measures_surv.mse {mlr3proba} | R Documentation

## Mean Squared Error Survival Measure

### Description

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.

### Dictionary

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")

### Meta Information

- Type: `"surv"`

- Range: [0, Inf)

- Minimize: `TRUE`

- Required prediction: `response`

### Super classes

`mlr3::Measure` -> `mlr3proba::MeasureSurv` -> `MeasureSurvMSE`

### Active bindings

`se`

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

### Methods

#### Public methods

- `MeasureSurvMSE$new()`

- `MeasureSurvMSE$clone()`

Inherited methods

- `mlr3::Measure$aggregate()`

- `mlr3::Measure$format()`

- `mlr3::Measure$help()`

- `mlr3::Measure$score()`

- `mlr3proba::MeasureSurv$print()`

#### Method `new()`

Creates a new instance of this R6 class.

##### Usage

    MeasureSurvMSE$new(se = FALSE)

##### Arguments

`se`

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

#### Method `clone()`

The objects of this class are cloneable with this method.

##### Usage

    MeasureSurvMSE$clone(deep = FALSE)

##### Arguments

`deep`

  Whether to make a deep clone.

### 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.nagelk_r2`, `mlr_measures_surv.oquigley_r2`, `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`

[Package mlr3proba version 0.4.2 Index]