Convert to a Spatiotemporal Classification Task — as_task_classif

Convert an object to a TaskClassifST. This is a S3 generic for the following objects:

TaskClassifST: Ensure the identity.
data.frame() and DataBackend: Provides an alternative to the constructor of TaskClassifST.
sf::sf: Extracts spatial meta data before construction.
TaskRegr: Calls convert_task().

Usage

as_task_classif_st(x, ...)

# S3 method for TaskClassifST
as_task_classif_st(x, clone = FALSE, ...)

# S3 method for data.frame
as_task_classif_st(
  x,
  target,
  id = deparse(substitute(x)),
  positive = NULL,
  coordinate_names,
  crs = NA_character_,
  coords_as_features = FALSE,
  label = NA_character_,
  ...
)

# S3 method for DataBackend
as_task_classif_st(
  x,
  target,
  id = deparse(substitute(x)),
  positive = NULL,
  coordinate_names,
  crs,
  coords_as_features = FALSE,
  label = NA_character_,
  ...
)

# S3 method for sf
as_task_classif_st(
  x,
  target = NULL,
  id = deparse(substitute(x)),
  positive = NULL,
  coords_as_features = FALSE,
  label = NA_character_,
  ...
)

Arguments

x: (any)
Object to convert.
...: (any)
Additional arguments.
clone: (logical(1))
If TRUE, ensures that the returned object is not the same as the input x.
target: (character(1))
Name of the target column.
id: (character(1))
Id for the new task. Defaults to the (deparsed and substituted) name of the data argument.
positive: (character(1))
Only for binary classification: Name of the positive class. The levels of the target columns are reordered accordingly, so that the first element of $class_names is the positive class, and the second element is the negative class.
coordinate_names: (character(1))
The column names of the coordinates in the data.
crs: (character(1))
Coordinate reference system. WKT2 or EPSG string.
coords_as_features: (logical(1))
If TRUE, coordinates are used as features. This is a shortcut for task$set_col_roles(c("x", "y"), role = "feature") with the assumption that the coordinates in the data are named "x" and "y".
label: (character(1))
Label for the new instance. Shown in as.data.table(mlr_tasks).

Value

TaskClassifST.

Examples

if (mlr3misc::require_namespaces(c("sf"), quietly = TRUE)) {
  library("mlr3")
  data("ecuador", package = "mlr3spatiotempcv")

  # data.frame
  as_task_classif_st(ecuador, target = "slides", positive = "TRUE",
    coords_as_features = FALSE,
    crs = "+proj=utm +zone=17 +south +datum=WGS84 +units=m +no_defs",
    coordinate_names = c("x", "y"))

  # sf
  ecuador_sf = sf::st_as_sf(ecuador, coords = c("x", "y"), crs = 32717)
  as_task_classif_st(ecuador_sf, target = "slides", positive = "TRUE")
}
#> <TaskClassifST:ecuador_sf> (751 x 11)
#> * Target: slides
#> * Properties: twoclass
#> * Features (10):
#>   - dbl (10): carea, cslope, dem, distdeforest, distroad,
#>     distslidespast, hcurv, log.carea, slope, vcurv
#> * Coordinates:
#>             X       Y
#>         <num>   <num>
#>   1: 712882.5 9560002
#>   2: 715232.5 9559582
#>   3: 715392.5 9560172
#>   4: 715042.5 9559312
#>   5: 715382.5 9560142
#>  ---                 
#> 747: 714472.5 9558482
#> 748: 713142.5 9560992
#> 749: 713322.5 9560562
#> 750: 715392.5 9557932
#> 751: 713802.5 9560862