mlr (version 2.3)

TuneControl: Create control structures for tuning.

Description

The following tuners are available: [object Object],[object Object],[object Object],[object Object],[object Object]

Some notes on irace: For resampling you have to pass a ResampleDesc, not a ResampleInstance. The resampling strategy is randomly instantiated n.instances times and these are the instances in the sense of irace (instances element of tunerConfig in irace). Also note that irace will always store its tuning results in a file on disk, see the package documentation for details on this and how to change the file path.

Usage

makeTuneControlCMAES(same.resampling.instance = TRUE, impute.val = NULL,
  start = NULL, tune.threshold = FALSE, tune.threshold.args = list(),
  log.fun = NULL, ...)
makeTuneControlGenSA(same.resampling.instance = TRUE, impute.val = NULL,
  start = NULL, tune.threshold = FALSE, tune.threshold.args = list(),
  log.fun = NULL, ...)
makeTuneControlGrid(same.resampling.instance = TRUE, impute.val = NULL,
  resolution = 10L, tune.threshold = FALSE, tune.threshold.args = list(),
  log.fun = NULL)
makeTuneControlIrace(impute.val = NULL, n.instances = 100L,
  show.irace.output = FALSE, tune.threshold = FALSE,
  tune.threshold.args = list(), log.fun = NULL, ...)
makeTuneControlRandom(same.resampling.instance = TRUE, maxit = 100L,
  tune.threshold = FALSE, tune.threshold.args = list(), log.fun = NULL)

Value

[TuneControl]. The specific subclass is one of TuneControlGrid, TuneControlRandom, TuneControlCMAES, TuneControlGenSA, TuneControlIrace.

See Also

Other tune: ModelMultiplexer, makeModelMultiplexer; getTuneResult; makeModelMultiplexerParamSet; makeTuneWrapper; tuneParams; tuneThreshold