View source: R/sperrorest_resampling.R
partition_factor_cv | R Documentation |
partition_factor_cv
creates a represampling object, i.e. a
set of sample indices defining cross-validation test and training sets,
where partitions are obtained by resampling at the level of groups of
observations as defined by a given factor variable. This can be used, for
example, to resample agricultural data that is grouped by fields, at the
agricultural field level in order to preserve spatial autocorrelation
within fields.
partition_factor_cv( data, coords = c("x", "y"), fac, nfold = 10, repetition = 1, seed1 = NULL, return_factor = FALSE )
data |
|
coords |
vector of length 2 defining the variables in |
fac |
either the name of a variable (column) in |
nfold |
number of partitions (folds) in |
repetition |
numeric vector: cross-validation repetitions to be
generated. Note that this is not the number of repetitions, but the indices
of these repetitions. E.g., use |
seed1 |
|
return_factor |
if |
A represampling object, see also partition_cv for details.
In this partitioning approach, the number of factor levels in fac
must be large enough for this factor-level resampling to make sense.
sperrorest, partition_cv, partition_factor, as.resampling.factor
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