runTaskMlr {OpenML}

Run mlr learner on OpenML task.

Description

Run task with a specified learner from mlr and produce predictions. By default, the evaluation measure contained in the task is used.

Usage

runTaskMlr(
  task,
  learner,
  measures = NULL,
  verbosity = NULL,
  seed = 1,
  scimark.vector = NULL,
  models = TRUE,
  ...
)

Arguments

task

[OMLTask]
An OpenML task.

learner

[Learner]
Learner from package mlr to run the task.

measures

[Measure]
Additional measures that should be computed.

verbosity

[integer(1)]
Print verbose output on console? Possible values are:
0: normal output,
1: info output,
2: debug output.
Default is set via setOMLConfig.

seed

[numeric(1)|OMLSeedParList ]
Set a seed to make the run reproducible. Default is 1 and sets the seed using set.seed(1).

scimark.vector

[numeric(6)]
Optional vector of performance measurements computed by the scientific SciMark benchmark. May be computed using the rscimark R package. Default is NULL, which means no performance measurements.

models

[logical(1)]
This argument is passed to benchmark. Should all fitted models be stored in the ResampleResult? Default is TRUE.

...

[any]
Further arguments that are passed to convertOMLTaskToMlr.

Value

[list] Named list with the following components:

run

The OMLRun object.

bmr

Benchmark result returned by benchmark.

flow

The generated OMLFlow object.

See Also

getOMLTask, makeLearner

Examples

# \dontrun{
#   library(mlr)
#   ## run a single flow (learner) on a single task
#   task = getOMLTask(57)
#   lrn = makeLearner("classif.rpart")
#   res = runTaskMlr(task, lrn)
#   ## the result "res" is a list, storing information on the actual "run", the
#   ## corresponding benchmark result "bmr" and the applied "flow"
# }