MeasureSurvAUC: Abstract Class for survAUC Measures

In mlr-org/mlr3proba: Probabilistic Supervised Learning for 'mlr3'

Abstract Class for survAUC Measures

Description

This is an abstract class that should not be constructed directly.

Parameter details

• integrated (logical(1))
  If TRUE (default), returns the integrated score (eg across time points); otherwise, not integrated (eg at a single time point).

• times (numeric())
  If integrated == TRUE then a vector of time-points over which to integrate the score. If integrated == FALSE then a single time point at which to return the score.

Super classes

mlr3::Measure -> mlr3proba::MeasureSurv -> MeasureSurvAUC

Methods

Public methods

• MeasureSurvAUC$new()

• MeasureSurvAUC$clone()

Inherited methods

• mlr3::Measure$aggregate()
• mlr3::Measure$format()
• mlr3::Measure$help()
• mlr3::Measure$print()
• mlr3::Measure$score()

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Method new()

Creates a new instance of this R6 class.

Usage

MeasureSurvAUC$new(
  id,
  properties = character(),
  label = NA_character_,
  man = NA_character_,
  param_set = ps()
)

Arguments

id

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

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).

label

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

man

(character(1))
String in the format ⁠[pkg]::[topic]⁠ pointing to a manual page for this object. The referenced help package can be opened via method ⁠$help()⁠.

param_set

(paradox::ParamSet)
Set of hyperparameters.

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Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureSurvAUC$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

mlr-org/mlr3proba documentation built on April 12, 2025, 4:38 p.m.