mlr3 (version 0.1.2)

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 may not be instantiated, and will be instantiated per task internally.

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

# NOT RUN {
tasks = list(tsk("iris"), tsk("sonar"))
learners = list(lrn("classif.featureless"), lrn("classif.rpart"))
resamplings = list(rsmp("cv"), rsmp("subsampling"))
benchmark_grid(tasks, learners, resamplings)
# }