ContextBatchTuning: Batch Tuning Context

In mlr-org/mlr3tuning: Hyperparameter Optimization for 'mlr3'

Batch Tuning Context

Description

A CallbackBatchTuning accesses and modifies data during the optimization via the ContextBatchTuning. See the section on active bindings for a list of modifiable objects. See callback_batch_tuning() for a list of stages that access ContextBatchTuning.

Super classes

mlr3misc::Context -> bbotk::ContextBatch -> ContextBatchTuning

Active bindings

xss

(list())
The hyperparameter configurations of the latest batch. Contains the values on the learner scale i.e. transformations are applied. See ⁠$xdt⁠ for the untransformed values.

design

(data.table::data.table)
The benchmark design of the latest batch.

benchmark_result

(mlr3::BenchmarkResult)
The benchmark result of the latest batch.

aggregated_performance

(data.table::data.table)
Aggregated performance scores and training time of the latest batch. This data table is passed to the archive. A callback can add additional columns which are also written to the archive.

result_learner_param_vals

(list())
The learner parameter values passed to instance$assign_result().

Methods

Public methods

• ContextBatchTuning$clone()

Inherited methods

• mlr3misc::Context$format()
• mlr3misc::Context$print()
• bbotk::ContextBatch$initialize()

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Method clone()

The objects of this class are cloneable with this method.

Usage

ContextBatchTuning$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

mlr-org/mlr3tuning documentation built on April 14, 2025, 1 a.m.