A simple LearnerRegr which only analyses the response during train, ignoring all features. If hyperparameter robust is FALSE (default), constantly predicts mean(y) as response and sd(y) as standard error. If robust is TRUE, median() and mad() are used instead of mean() and sd(), respectively.

## Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

### Method importance()

All features have a score of 0 for this learner.

### Method clone()

The objects of this class are cloneable with this method.

#### Usage

LearnerRegrFeatureless\$clone(deep = FALSE)

#### Arguments

deep

Whether to make a deep clone.