R/summary_functions.R
summary.sperroresterror.Rdsummary.sperroresterror calculates mean, standard deviation,
median etc. of the calculated error measures at the specified level
(overall, repetition, or fold). summary.sperrorestreperror does the same
with the pooled error, at the overall or repetition level.
# S3 method for class 'sperroresterror'
summary(object, level = 0, pooled = TRUE, na.rm = TRUE, ...)sperroresterror resp. sperrorestcombinederror error object
calculated by sperrorest
Level at which errors are summarized: 0: overall (i.e. across all repetitions); 1: repetition; 2: fold
If TRUE (default), mean and standard deviation etc are
calculated between fold-level error estimates. If FALSE, apply first a
weighted.mean among folds before calculating mean, standard deviation etc
among repetitions. See also Details.
Remove NA values? See mean etc.
additional arguments (currently ignored)
Depending on the level of aggregation, a list or data.frame with
mean, and at level 0 also standard deviation, median and IQR of the error
measures.
Let's use an example to explain the error_rep argument. E.g.,
assume we are using 100-repeated 10-fold cross-validation. If error_rep = TRUE (default), the mean and standard deviation calculated when
summarizing at level = 0 are calculated across the error estimates
obtained for each of the 100*10 = 1000 folds. If error_rep = FALSE,
mean and standard deviation are calculated across the 100 repetitions,
using the weighted average of the fold-level errors to calculate an error
value for the entire sample. This will essentially not affect the mean
value but of course the standard deviation of the error.
error_rep = FALSE is not recommended, it is mainly for testing purposes;
when the test sets are small (as in leave-one-out cross-validation, in the
extreme case), consider running sperrorest with error_rep = TRUE and
examine only the error_rep component of its result.