Description Usage Arguments Details Value See Also Examples
get_fold_data
returns a list of training and test occurrence and
background data fold(s) for one or more species.
1 | get_fold_data(species, fold_type, k)
|
species |
dataframe or character vector. Row from the dataframe returned
by |
fold_type |
character. Type of partitioning you want to use, default is
|
k |
integer vector. Numbers of the folds you want to get data for, if
you want all folds use |
The different fold_type
are:
"disc"
: 5-fold disc partitioning of occurrences with pairwise
distance sampled and buffer filtered random background points, equivalent
to calling kfold_occurrence_background
with
occurrence_fold_type = "disc", k = 5, pwd_sample = TRUE,
background_buffer = 200*1000
"grid_4"
and "grid_9"
: 4-fold and 9-fold grid partitioning of
occurrences with pairwise distance sampled and buffer filtered random
background points, equivalent to calling
kfold_occurrence_background
with occurrence_fold_type =
"grid", k = 4, pwd_sample = TRUE, background_buffer = 200*1000
"random"
: 5-fold random partitioning of occurrences and random
background points, equivalent to calling
kfold_occurrence_background
with occurrence_fold_type =
"random", k = 5, pwd_sample = FALSE, background_buffer = 0
"targetgroup"
: same way of partitioning as the "random"
folds
but instead of random background points, a random subset of all occurrences
points was used creating a targetgroup background points set which has the
same sampling bias as the entire dataset.
A 5 element list with fold data filled in for all k
. Fold data
consists of a list with 4 elements: occurrence_training
,
occurrence_test
, background_training
and
background_test
.
list_species
lapply_kfold_species
lapply_species
kfold_data
1 2 3 4 5 6 7 8 9 | ## Not run:
aba_folds <- get_fold_data("Abalistes stellatus", "random", k = 1:5)
k1 <- aba_folds[[1]]
k1$occurrence_training
k1$occurrence_test
k1$background_training
k1$background_test
## End(Not run)
|
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