View source: R/sperrorest_misc.R
add.distance | R Documentation |
Add distance information to resampling objects
add.distance(object, ...) ## S3 method for class 'resampling' add.distance(object, data, coords = c("x", "y"), ...) ## S3 method for class 'represampling' add.distance(object, data, coords = c("x", "y"), mode = "future", ...)
object |
resampling or represampling object. |
... |
Additional arguments to dataset_distance and add.distance.resampling, respectively. |
data |
|
coords |
(ignored by |
mode |
Use |
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.
A resampling or represampling object containing an additional.
$distance
component in each resampling object. The distance
component
is a single numeric value indicating, for each train
/ test
pair, the
(by default, mean) nearest-neighbour distance between the two sets.
dataset_distance represampling resampling
# Muenchow et al. (2012), see ?ecuador nsp.parti <- partition_cv(ecuador) sp.parti <- partition_kmeans(ecuador) nsp.parti <- add.distance(nsp.parti, data = ecuador) sp.parti <- add.distance(sp.parti, data = ecuador) # non-spatial partioning: very small test-training distance: nsp.parti[[1]][[1]]$distance # spatial partitioning: more substantial distance, depending on number of # folds etc. sp.parti[[1]][[1]]$distance
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