randomFolds | R Documentation |
Create random folds for cross validation.
randomFolds(data, k, only_presence = FALSE, seed = NULL)
data |
SWD object that will be used to train the model. |
k |
integer. Number of fold used to create the partition. |
only_presence |
logical, if |
seed |
integer. The value used to set the seed for the fold partition. |
When only_presence = FALSE
, the proportion of presence and absence
is preserved.
list with two matrices, the first for the training and the second for
the testing dataset. Each column of one matrix represents a fold with
TRUE
for the locations included in and FALSE
excluded from the partition.
Sergio Vignali
# Acquire environmental variables
files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
pattern = "grd", full.names = TRUE)
predictors <- terra::rast(files)
# Prepare presence and background locations
p_coords <- virtualSp$presence
bg_coords <- virtualSp$background
data <- prepareSWD(species = "Virtual species", p = p_coords, a = bg_coords,
env = predictors, categorical = "biome")
# Create 4 random folds splitting presence and absence locations
folds <- randomFolds(data, k = 4)
# Create 4 random folds splitting only the presence locations
folds <- randomFolds(data, k = 4, only_presence = TRUE)
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