cvFolds | R Documentation |
Split observations or groups of observations into K
folds to be used
for (repeated) K
-fold cross-validation. K
should thereby be
chosen such that all folds are of approximately equal size.
cvFolds(
n,
K = 5,
R = 1,
type = c("random", "consecutive", "interleaved"),
grouping = NULL
)
n |
an integer giving the number of observations to be split into
folds. This is ignored if |
K |
an integer giving the number of folds into which the observations
should be split (the default is five). Setting |
R |
an integer giving the number of replications for repeated
|
type |
a character string specifying the type of folds to be
generated. Possible values are |
grouping |
a factor specifying groups of observations. If supplied, the data are split according to the groups rather than individual observations such that all observations within a group belong to the same fold. |
An object of class "cvFolds"
with the following components:
n |
an integer giving the number of observations or groups. |
K |
an integer giving the number of folds. |
R |
an integer giving the number of replications. |
subsets |
an integer matrix in which each column contains a permutation of the indices of the observations or groups. |
which |
an integer vector giving the fold for each permuted observation or group. |
grouping |
a list giving the indices of the observations belonging to each group. This is only returned if a grouping factor has been supplied. |
Andreas Alfons
cvFit
, cvSelect
, cvTuning
set.seed(1234) # set seed for reproducibility
cvFolds(20, K = 5, type = "random")
cvFolds(20, K = 5, type = "consecutive")
cvFolds(20, K = 5, type = "interleaved")
cvFolds(20, K = 5, R = 10)
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