mlr3: benchmark_grid – R documentation

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benchmark_grid

Generate a Benchmark Grid Design

Description

Takes a lists of Task, a list of Learner and a list of Resampling to generate a design in an expand.grid() fashion (a.k.a. cross join or Cartesian product).

Resampling strategies are not allowed to be instantiated when passing the argument, and instead will be instantiated per task internally. The only exception to this rule applies if all tasks have exactly the same number of rows, and the resamplings are all instantiated for such tasks.

Usage

benchmark_grid(tasks, learners, resamplings)

Arguments

`tasks`	(list of Task).
`learners`	(list of Learner).
`resamplings`	(list of Resampling).

Value

(data.table::data.table()) with the cross product of the input vectors.

Examples

tasks = list(tsk("penguins"), tsk("sonar"))
learners = list(lrn("classif.featureless"), lrn("classif.rpart"))
resamplings = list(rsmp("cv"), rsmp("subsampling"))
benchmark_grid(tasks, learners, resamplings)

mlr3

Machine Learning in R - Next Generation

v0.11.0

LGPL-3

Authors

Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>), Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [aut], Marc Becker [ctb] (<https://orcid.org/0000-0002-8115-0400>)

Initial release