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

  1. TaskClassifST: Ensure the identity.

  2. data.frame() and DataBackend: Provides an alternative to the constructor of TaskClassifST.

  3. sf::sf: Extracts spatial meta data before construction.

  4. TaskRegr: Calls convert_task().

Usage

as_task_classif_st(x, ...)

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

# S3 method for class '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 class '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 class '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