A simple mlr3misc::Dictionary storing objects of class Resampling.
Each resampling has an associated help page, see mlr_resamplings_[id].
This dictionary can get populated with additional resampling strategies by add-on packages.
For a more convenient way to retrieve and construct resampling strategies, see rsmp()/rsmps().
Format
R6::R6Class object inheriting from mlr3misc::Dictionary.
Methods
See mlr3misc::Dictionary.
S3 methods
as.data.table(dict, ..., objects = FALSE)
mlr3misc::Dictionary ->data.table::data.table()
Returns adata.table::data.table()with columns "key", "label", "params", and "iters". Ifobjectsis set toTRUE, the constructed objects are returned in the list column namedobject.
See also
Sugar functions: rsmp(), rsmps()
Other Dictionary:
mlr_learners,
mlr_measures,
mlr_task_generators,
mlr_tasks
Other Resampling:
Resampling,
mlr_resamplings_bootstrap,
mlr_resamplings_custom,
mlr_resamplings_custom_cv,
mlr_resamplings_cv,
mlr_resamplings_holdout,
mlr_resamplings_insample,
mlr_resamplings_loo,
mlr_resamplings_repeated_cv,
mlr_resamplings_subsampling
Examples
as.data.table(mlr_resamplings)
#> Key: <key>
#> key label params iters
#> <char> <char> <list> <int>
#> 1: bootstrap Bootstrap ratio,repeats 30
#> 2: custom Custom Splits NA
#> 3: custom_cv Custom Split Cross-Validation NA
#> 4: cv Cross-Validation folds 10
#> 5: holdout Holdout ratio 1
#> 6: insample Insample Resampling 1
#> 7: loo Leave-One-Out NA
#> 8: repeated_cv Repeated Cross-Validation folds,repeats 100
#> 9: subsampling Subsampling ratio,repeats 30
mlr_resamplings$get("cv")
#>
#> ── <ResamplingCV> : Cross-Validation ───────────────────────────────────────────
#> • Iterations: 10
#> • Instantiated: FALSE
#> • Parameters: folds=10
rsmp("subsampling")
#>
#> ── <ResamplingSubsampling> : Subsampling ───────────────────────────────────────
#> • Iterations: 30
#> • Instantiated: FALSE
#> • Parameters: ratio=0.6667, repeats=30