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 based on a chosen metric (note that the metric is defined when tuning the workflows, it can not be changed at this stage). 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()