This Learner specializes Learner for regression problems.

Predefined learners can be found in the Dictionary mlr_learners.


R6::R6Class object inheriting from Learner.


l = LearnerRegr$new(id, param_set = ParamSet$new(), param_vals = list(), predict_types = character(),
     feature_types = character(), properties = character(), data_formats = "data.table", packages = character())

For a description of the arguments, see Learner. task_type is set to "regr". Possible values for predict_types are a subset of c("response", "se").


See Learner.


See Learner.

See also

Example regression learner: regr.rpart.

Other Learner: LearnerClassif, Learner, mlr_learners


# get all regression learners from mlr_learners: lrns = mlr_learners$mget(mlr_learners$keys("^regr")) names(lrns)
#> [1] "regr.featureless" "regr.rpart"
# get a specific learner from mlr_learners: lrn = mlr_learners$get("regr.rpart") print(lrn)
#> <LearnerRegrRpart:regr.rpart> #> Parameters: xval=0 #> Packages: rpart #> Predict Type: response #> Feature types: logical, integer, numeric, character, factor, ordered #> Properties: importance, missings, selected_features, weights