Add distance information to resampling objects
add.distance(object, ...) # S3 method for resampling add.distance(object, data, coords = c("x", "y"), ...) # S3 method for represampling add.distance(object, ...)
object | resampling or represampling object. |
---|---|
... | Additional arguments to dataset_distance and add.distance.resampling, respectively. |
data |
|
coords | (ignored by |
A resampling or represampling object
containing an additional.
$distance
component in each resampling object.
The distance
component is a single numeric value indicating, for
each train
/ test
pair, the (by default, mean)
nearest-neighbour distance between the two sets.
Nearest-neighbour distances are calculated for each sample in the
test set. These nrow(???$test)
nearest-neighbour distances are then
averaged. Aggregation methods other than mean
can be chosen using
the fun
argument, which will be passed on to
dataset_distance.
dataset_distance represampling resampling
data(ecuador) # Muenchow et al. (2012), see ?ecuador nsp.parti <- partition_cv(ecuador) sp.parti <- partition_kmeans(ecuador) nsp.parti <- add.distance(nsp.parti, ecuador) sp.parti <- add.distance(sp.parti, ecuador) # non-spatial partioning: very small test-training distance: nsp.parti[[1]][[1]]$distance#> [1] 53.79223# spatial partitioning: more substantial distance, depending on number of # folds etc. sp.parti[[1]][[1]]$distance#> [1] 390.1742