label_artificial_data_classif: Label a dataset using a supplied learner.
In pfistfl/distillery: Compress arbitrary mlr3 models into keras models

Description Usage Arguments Value

View source: R/label_data.R

Uses the provided learner in order to predict on the provided task's features. 'prob = TRUE' implements Dark Knowledge as implmented by Hinton, 2015. If 'prob', predicts probabilities, else response. The mixing parameter 'alpha' corresponds to a trade-off between the predicted target and the actual target, where 0 only uses predicted targets (default) and 1 only uses the true label.

1	label_artificial_data_classif(task, teacher, prob = TRUE, alpha = 0)

`task`	['Task'] Task to create labels for.
`teacher`	['Learner'] Trained learner to compress into a neural network.
`prob`	['logical'] Predict probabilities instead of response? Default: True.
`alpha`	['numeric'] Specifies a convex-combination of labels predicted by the learner (alpha = 0) and labels of the observation before swapping. Default: 0 (only learner predictions)