A simple ensemble is a collection of workflows for which predictions will be combined in a simple way (e.g. by taking either the mean or median). Usually these workflows will consists each of the best version of a given model algorithm following tuning. The workflows are fitted to the full training dataset before making predictions.
simple_ensemble(...)an empty simple_ensemble. This is a tibble with columns:
wflow_id: the name of the workflows for which the best model was
chosen
workflow: the trained workflow objects
metrics: metrics based on the crossvalidation resampling used
to tune the models
not used, this function just creates an empty simple_ensemble
object. Members are added with add_best_candidates()