When building a model on a data set and re-predicting the same data, the
performance estimate from those predictions is often call the
"apparent" performance of the model. This estimate can be wildly
optimistic. "Apparent sampling" here means that the analysis and
assessment samples are the same. These resamples are sometimes used in
the analysis of bootstrap samples and should otherwise be
avoided like ol sushi.
Usage
apparent(data, ...)
Arguments
data
A data frame.
...
Not currently used.
Value
An tibble with a single row and classes `apparent`,
`rset`, `tbl_df`, `tbl`, and `data.frame`. The
results include a column for the data split objects and one column
called `id` that has a character string with the resample identifier.