Dictionary of Resampling Strategies

Source: R/mlr_resamplings.R

A simple Dictionary storing objects of class Resampling. Each resampling has an associated help page, see mlr_resamplings_[id].

Format

R6::R6Class object.

Methods

• get(key, ...)
  (character(1), ...) -> any
  Retrieves object with key key from the dictionary.

• mget(keys, ...)
  (character(), ...) -> named list()
  Retrieves objects with keys keys from the dictionary, returns them in a list named with keys.

• has(keys)
character() -> logical()
  Returns a logical vector with TRUE at its i-th position, if the i-th key exists.

• keys(pattern)
character(1) -> character()
  Returns all keys which comply to the regular expression pattern.

• add(key, value)
  (character(1), any) -> self
  Adds object value to the dictionary with key key, potentially overwriting a previously stored value.

• remove(key)
character() -> self
  Removes object with key key from the dictionary.

S3 methods

• as.data.table(dict)
  Dictionary -> data.table::data.table()
  Returns a data.table() with fields "key", "hyperpars", and "iters" as columns.

See also

Other Dictionary: Dictionary, mlr_generators, mlr_learners, mlr_measures, mlr_tasks

Other Resampling: Resampling

Examples

as.data.table(mlr_resamplings)
#>            key              hyperpars iters
#> 1:   bootstrap stratify,repeats,ratio    30
#> 2:      custom                            0
#> 3:          cv         stratify,folds    10
#> 4:     holdout         stratify,ratio     1
#> 5: repeated_cv stratify,repeats,folds   100
#> 6: subsampling stratify,repeats,ratio    30
mlr_resamplings$get("cv")
#> <ResamplingCV> with 10 iterations
#> Instantiated: FALSE
#> Parameters: folds=10
#> 
#> Public: clone, duplicated_ids, format, hash, id, instance,
#>   instantiate, is_instantiated, iters, param_set, task_hash, test_set,
#>   train_set