Defines how the hyperparameter tuning should be conducted

makeHyperControl(mlr.control = NULL, resampling = NULL, measures = NULL,
  par.config = NULL)

Arguments

mlr.control

[TuneControl] Control object for search method. Also selects the optimization algorithm for tuning.

resampling

[ResampleDesc] The resampling determines how the performance is obtained during tuning.

measures

[Measure | list of Measure] Performance measure(s) to evaluate. Default is the default measure for the task, see here getDefaultMeasure.

par.config

[ParConfig] The Parameter Configuration

Value

[HyperControl]

See also

Other HyperControl: getHyperControlMeasures, getHyperControlMlrControl, getHyperControlResampling, setHyperControlMeasures, setHyperControlMlrControl, setHyperControlResampling

Examples

hyper.control = makeHyperControl( mlr.control = makeTuneControlRandom(maxit = 5), resampling = cv2, measures = acc ) hyperopt(task = iris.task, learner = "classif.svm", hyper.control = hyper.control)
#> [Tune] Started tuning learner classif.svm for parameter set:
#> Type len Def Constr Req Tunable Trafo #> cost numeric - 0 -15 to 15 - TRUE Y #> gamma numeric - -2 -15 to 15 - TRUE Y
#> With control class: TuneControlRandom
#> Imputation value: -0
#> [Tune-x] 1: cost=1.74e+03; gamma=0.000271
#> Resampling: cross-validation
#> Measures: acc
#> [Tune-y] 1: acc.test.mean=0.9666667; time: 0.0 min
#> [Tune-x] 2: cost=85.7; gamma=0.000866
#> Resampling: cross-validation
#> Measures: acc
#> [Tune-y] 2: acc.test.mean=0.9666667; time: 0.0 min
#> [Tune-x] 3: cost=8.7e-05; gamma=0.0179
#> Resampling: cross-validation
#> Measures: acc
#> [Tune-y] 3: acc.test.mean=0.2866667; time: 0.0 min
#> [Tune-x] 4: cost=0.00639; gamma=0.00551
#> Resampling: cross-validation
#> Measures: acc
#> [Tune-y] 4: acc.test.mean=0.2866667; time: 0.0 min
#> [Tune-x] 5: cost=0.157; gamma=0.000162
#> Resampling: cross-validation
#> Measures: acc
#> [Tune-y] 5: acc.test.mean=0.2866667; time: 0.0 min
#> [Tune] Result: cost=85.7; gamma=0.000866 : acc.test.mean=0.9666667
#> Tune result: #> Op. pars: cost=85.7; gamma=0.000866 #> acc.test.mean=0.9666667