This task specializes Task and TaskSupervised for spatiotemporal classification problems. The target column is assumed to be a factor. The task_type is set to "classif" and "spatiotemporal".

A spatial example task is available via tsk("ecuador"), a spatiotemporal one via tsk("cookfarm_mlr3").

The coordinate reference system passed during initialization must match the one which was used during data creation, otherwise offsets of multiple meters may occur. By default, coordinates are not used as features. This can be changed by setting coords_as_features = TRUE.

Other Task: TaskRegrST, mlr_tasks_cookfarm_mlr3, mlr_tasks_diplodia, mlr_tasks_ecuador

## Super classes

mlr3::Task -> mlr3::TaskSupervised -> mlr3::TaskClassif -> TaskClassifST

## Active bindings

crs

(character(1))
Returns coordinate reference system of task.

coordinate_names

(character())
Coordinate names.

coords_as_features

(logical(1))
If TRUE, coordinates are used as features. This is a shortcut for task$set_col_roles(c("x", "y"), role = "feature") with the assumption that the coordinates in the data are named "x" and "y". ## Methods ### Public methods Inherited methods ### Method new() Create a new spatiotemporal resampling Task #### Usage TaskClassifST$new(
id,
backend,
target,
positive = NULL,
label = NA_character_,
coordinate_names,
crs = NA_character_,
coords_as_features = FALSE,
extra_args = list()
)

#### Arguments

id

(character(1))
Identifier for the new instance.

backend

(DataBackend)
Either a DataBackend, or any object which is convertible to a DataBackend with as_data_backend(). E.g., am sf will be converted to a DataBackendDataTable.

target

(character(1))
Name of the target column.

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 $class_names is the positive class, and the second element is the negative class. label (character(1)) Label for the new instance. Shown in as.data.table(mlr_tasks). coordinate_names (character(1)) The column names of the coordinates in the data. crs (character(1)) Coordinate reference system. WKT2 or EPSG string. coords_as_features (logical(1)) If TRUE, coordinates are used as features. This is a shortcut for task$set_col_roles(c("x", "y"), role = "feature") with the assumption that the coordinates in the data are named "x" and "y".

extra_args

(named list())
Named list of constructor arguments, required for converting task types via convert_task().

### Method coordinates()

Returns coordinates of observations.

#### Returns

data.table::data.table()

### Method clone()

The objects of this class are cloneable with this method.

TaskClassifST$clone(deep = FALSE) #### Arguments deep Whether to make a deep clone. ## Examples # \donttest{ if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) { task = as_task_classif_st(ecuador, target = "slides", positive = "TRUE", coordinate_names = c("x", "y") ) # passing objects of class 'sf' is also supported data_sf = sf::st_as_sf(ecuador, coords = c("x", "y")) task = as_task_classif_st(data_sf, target = "slides", positive = "TRUE") task$task_type
task$formula() task$class_names
task$positive task$negative
task$coordinates() task$coordinate_names
}
#> [1] "X" "Y"
# }