TaskClassifST: Spatiotemporal Classification Task

In mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem

Spatiotemporal Classification Task

Description

This task specializes mlr3::TaskClassif for spatiotemporal classification problems.

A spatial example task is available via tsk("ecuador").

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.

Super classes

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

Active bindings

crs

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

coordinate_names

(character())
Returns coordinate names.

coords_as_features

(logical(1))
If TRUE, coordinates are used as features.

Methods

Public methods

• TaskClassifST$new()

• TaskClassifST$coordinates()

• TaskClassifST$print()

• TaskClassifST$clone()

Inherited methods

• mlr3::Task$add_strata()
• mlr3::Task$cbind()
• mlr3::Task$data()
• mlr3::Task$divide()
• mlr3::Task$filter()
• mlr3::Task$format()
• mlr3::Task$formula()
• mlr3::Task$head()
• mlr3::Task$help()
• mlr3::Task$levels()
• mlr3::Task$missings()
• mlr3::Task$rbind()
• mlr3::Task$rename()
• mlr3::Task$select()
• mlr3::Task$set_col_roles()
• mlr3::Task$set_levels()
• mlr3::Task$set_row_roles()
• mlr3::TaskClassif$droplevels()
• mlr3::TaskClassif$truth()

---

Method new()

Creates a new instance of this R6 class. The function as_task_classif_st() provides an alternative way to construct classification tasks.

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

(mlr3::DataBackend)
Either a mlr3::DataBackend, or any object which is convertible to a mlr3::DataBackend with mlr3::as_data_backend(). E.g., am sf will be converted to a mlr3::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.

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 mlr3::convert_task().

---

Method coordinates()

Returns coordinates of observations.

Usage

TaskClassifST$coordinates(row_ids = NULL)

Arguments

row_ids

(integer()) Vector of rows indices as subset of task$row_ids.

Returns

data.table::data.table()

---

Method print()

Print the task.

Usage

TaskClassifST$print(...)

Arguments

...

Arguments passed to the ⁠$print()⁠ method of the superclass.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TaskClassifST$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

mlr3spatial documentation built on Aug. 12, 2025, 1:08 a.m.