Augment data with holdout predictionsSource:
tune objects that use resampling, these
augment() methods will add
one or more columns for the hold-out predictions (i.e. from the assessment
A data frame with a single row that indicates what tuning parameters should be used to generate the predictions (for
tune_*()objects only). If
select_best(x)will be used.
Not currently used.
For some resampling methods where rows may be replicated in multiple assessment sets, the prediction columns will be averages of the holdout results. Also, for these methods, it is possible that all rows of the original data do not have holdout predictions (like a single bootstrap resample). In this case, all rows are return and a warning is issued.
For objects created by
last_fit(), the test set data and predictions are
augment() methods, the predicted values for regression models
are in a column called
.pred instead of
.fitted (to be consistent with
other tidymodels conventions).
For regression problems, an additional
.resid column is added to the