id
:: character(1)
Stores the identifier of the learner.
task_type
:: character(1)
Stores the type of class this learner can operate on, e.g. "classif"
or "regr"
.
A complete list of task types is stored in mlr_reflections$task_types
.
param_set
:: paradox::ParamSet
Description of available hyperparameters and hyperparameter settings.
predict_types
:: character()
Stores the possible predict types the learner is capable of.
A complete list of candidate predict types, grouped by task type, is stored in mlr_reflections$learner_predict_types
.
predict_type
:: character(1)
Stores the currently selected predict type. Must be an element of l$predict_types
.
feature_types
:: character()
Stores the feature types the learner can handle, e.g. "logical"
, "numeric"
, or "factor"
.
A complete list of candidate feature types, grouped by task type, is stored in mlr_reflections$task_feature_types
.
properties
:: character()
Stores a set of properties/capabilities the learner has.
A complete list of candidate properties, grouped by task type, is stored in mlr_reflections$learner_properties
.
packages
:: character()
Stores the names of required packages.
fallback
:: (Learner | NULL
)
Optionally stores a second Learner which is activated as fallback if this first Learner fails during
train or predict.
This mechanism is disabled unless you explicitly assign a learner to this slot.
Additionally, you need to catch raised exceptions via encapsulation, see mlr_control()
.
hash
:: character(1)
Hash (unique identifier) for this object.