This measure specializes Measure for survival problems.

  • task_type is set to "surv".

  • Possible values for predict_type are "distr", "lp", "crank", and "response".

Predefined measures can be found in the dictionary mlr3::mlr_measures.

See also

Default survival measures: surv.harrellC

Other Measure: MeasureDens

Super class

mlr3::Measure -> MeasureSurv

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

MeasureSurv$new(
  id,
  range,
  minimize = NA,
  aggregator = NULL,
  properties = character(),
  predict_type = "distr",
  task_properties = character(),
  packages = character()
)

Arguments

id

(character(1))
Identifier for the new instance.

range

(numeric(2))
Feasible range for this measure as c(lower_bound, upper_bound). Both bounds may be infinite.

minimize

(logical(1))
Set to TRUE if good predictions correspond to small values, and to FALSE if good predictions correspond to large values. If set to NA (default), tuning this measure is not possible.

aggregator

(function(x))
Function to aggregate individual performance scores x where x is a numeric vector. If NULL, defaults to mean().

properties

(character())
Properties of the measure. Must be a subset of mlr_reflections$measure_properties. Supported by mlr3:

  • "requires_task" (requires the complete Task),

  • "requires_learner" (requires the trained Learner),

  • "requires_train_set" (requires the training indices from the Resampling), and

  • "na_score" (the measure is expected to occasionally return NA or NaN).

predict_type

(character(1))
Required predict type of the Learner. Possible values are stored in mlr_reflections$learner_predict_types.

task_properties

(character())
Required task properties, see Task.

packages

(character())
Set of required packages. A warning is signaled by the constructor if at least one of the packages is not installed, but loaded (not attached) later on-demand via requireNamespace().