A simple LearnerClassif which only analyses the labels during train, ignoring all features. Hyperparameter method determines the mode of operation during prediction:

mode:

Predicts the most frequent label. If there are two or more labels tied, randomly selects one per prediction.

sample:

Randomly predict a label uniformly.

weighed.sample:

Randomly predict a label, with probability estimated from the training distribution.

## 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.

#### Returns

character(0).

### Method clone()

The objects of this class are cloneable with this method.

#### Usage

LearnerClassifFeatureless\$clone(deep = FALSE)

#### Arguments

deep

Whether to make a deep clone.