A simple Dictionary storing objects of class Learner. Each learner has an associated help page, see mlr_learners_[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

See also

Examples

as.data.table(mlr_learners)
#> key feature_types #> 1: classif.debug logical,integer,numeric,character,factor,ordered #> 2: classif.featureless logical,integer,numeric,character,factor,ordered #> 3: classif.rpart logical,integer,numeric,character,factor,ordered #> 4: regr.featureless logical,integer,numeric,character,factor,ordered #> 5: regr.rpart logical,integer,numeric,character,factor,ordered #> packages properties #> 1: missings #> 2: importance,missings,multiclass,selected_features,twoclass #> 3: rpart importance,missings,multiclass,selected_features,twoclass,weights #> 4: stats importance,missings,selected_features #> 5: rpart importance,missings,selected_features,weights #> predict_types #> 1: response,prob #> 2: response,prob #> 3: response,prob #> 4: response,se #> 5: response
mlr_learners$get("classif.featureless")
#> <LearnerClassifFeatureless:classif.featureless> #> Parameters: method=mode #> Packages: - #> Predict Type: response #> Feature types: logical, integer, numeric, character, factor, ordered #> Properties: importance, missings, multiclass, selected_features, #> twoclass #> #> Public: clone(), data_formats, fallback, feature_types, hash, id, #> importance(), model, packages, param_set, params(), predict_type, #> predict_types, predict(), properties, selected_features(), task_type, #> train()