Functions for handling represampling
objects, i.e. list
s of
resampling objects.
as.represampling(object, ...) # S3 method for list as.represampling(object, ...) # S3 method for represampling print(x, ...) is_represampling(object)
object | object of class |
---|---|
... | currently not used. |
x | object of class |
as.represampling
methods return an object of class
represampling
with the contents of object
.
represampling
objects are (names) lists of
resampling objects. Such objects are typically created by
partition_cv, partition_kmeans,
represampling_disc_bootstrap and related functions.
In r
-repeated k
-fold cross-validation, for example, the
corresponding represampling
object has length r
, and each of
its r
resampling objects has length k
.
as.resampling_list
coerces object
to class represampling
while coercing its elements to resampling objects.
Some validity checks are performed.
resampling, partition_cv, partition_kmeans, represampling_disc_bootstrap, etc.
data(ecuador) # Muenchow et al. (2012), see ?ecuador # Partitioning by elevation classes in 200 m steps: fac <- factor( as.character( floor( ecuador$dem / 300 ) ) ) summary(fac)#> 10 5 6 7 8 9 #> 4 21 246 255 147 78parti <- as.resampling(fac) # a list of lists specifying sets of training and test sets, # using each factor at a time as the test set: str(parti)#> List of 6 #> $ 10:List of 2 #> ..$ train: int [1:747] 1 2 3 4 5 6 7 8 9 10 ... #> ..$ test : int [1:4] 535 566 684 734 #> $ 5 :List of 2 #> ..$ train: int [1:730] 1 2 3 4 5 6 7 8 9 10 ... #> ..$ test : int [1:21] 42 77 93 106 115 139 250 332 385 405 ... #> $ 6 :List of 2 #> ..$ train: int [1:505] 2 4 7 8 9 12 13 14 15 17 ... #> ..$ test : int [1:246] 1 3 5 6 10 11 16 19 23 29 ... #> $ 7 :List of 2 #> ..$ train: int [1:496] 1 3 5 6 7 8 10 11 12 13 ... #> ..$ test : int [1:255] 2 4 9 18 20 22 24 26 28 30 ... #> $ 8 :List of 2 #> ..$ train: int [1:604] 1 2 3 4 5 6 7 9 10 11 ... #> ..$ test : int [1:147] 8 12 14 15 21 25 27 32 46 54 ... #> $ 9 :List of 2 #> ..$ train: int [1:673] 1 2 3 4 5 6 8 9 10 11 ... #> ..$ test : int [1:78] 7 13 17 35 44 75 78 79 88 97 ... #> - attr(*, "class")= chr "resampling"summary(parti)#> n.train n.test #> 10 747 4 #> 5 730 21 #> 6 505 246 #> 7 496 255 #> 8 604 147 #> 9 673 78