mlr3tuning (version 0.2.0)

ObjectiveTuning: ObjectiveTuning

Description

Stores the objective function that estimates the performance of hyperparameter configurations. This class is usually constructed internally by the TuningInstanceSingleCrit / TuningInstanceMultiCrit.

Super class

bbotk::Objective -> ObjectiveTuning

Public fields

task

(mlr3::Task).

learner

(mlr3::Learner).

resampling

(mlr3::Resampling).

measures

(list of mlr3::Measure).

store_models

(logical(1)).

store_resample_results

(logical(1)).

Methods

Public methods

• ObjectiveTuning$new()

• ObjectiveTuning$clone()

• bbotk::Objective$eval()

• bbotk::Objective$eval_dt()

• bbotk::Objective$eval_many()

• bbotk::Objective$format()

• bbotk::Objective$print()

Method new()

Creates a new instance of this R6 class.

Usage

ObjectiveTuning$new(
  task,
  learner,
  resampling,
  measures,
  store_models = FALSE,
  check_values = TRUE,
  store_resample_results = TRUE
)

Arguments

task

(mlr3::Task) Task to operate on.

learner

(mlr3::Learner).

resampling

(mlr3::Resampling) Uninstantiated resamplings are instantiated during construction so that all configurations are evaluated on the same data splits.

measures

(list of mlr3::Measure) Measures to optimize. If NULL, mlr3's default measure is used.

store_models

(logical(1)).

check_values

(logical(1)) Should parameters before the evaluation and the results be checked for validity?

store_resample_results

(logical(1)) Store resample results in archive?

Method clone()

The objects of this class are cloneable with this method.

Usage

ObjectiveTuning$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.