TaskRegrST {mlr3spatial} | R Documentation |
This task specializes TaskRegr for spatiotemporal regression problems.
A spatial example task is available 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
.
mlr3::Task
-> mlr3::TaskSupervised
-> mlr3::TaskRegr
-> TaskRegrST
crs
(character(1)
)
Returns coordinate reference system of the task.
coordinate_names
(character()
)
Returns coordinate names.
coords_as_features
(logical(1)
)
If TRUE
, coordinates are used as features.
mlr3::Task$add_strata()
mlr3::Task$cbind()
mlr3::Task$data()
mlr3::Task$droplevels()
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$set_row_roles()
mlr3::TaskRegr$truth()
new()
Creates a new instance of this R6 class.
The function as_task_regr_st()
provides an alternative way to construct classification tasks.
TaskRegrST$new( id, backend, target, label = NA_character_, coordinate_names, crs = NA_character_, coords_as_features = FALSE, extra_args = list() )
id
(character(1)
)
Identifier for the new instance.
backend
(DataBackend)
Either a DataBackend, or any object which is convertible to a DataBackend with as_data_backend()
.
E.g., am sf
will be converted to a DataBackendDataTable.
target
(character(1)
)
Name of the target column.
label
(character(1)
)
Label for the new instance.
coordinate_names
(character(1)
)
The column names of the coordinates in the data.
crs
(character(1)
)
Coordinate reference system.
WKT2 or EPSG string.
coords_as_features
(logical(1)
)
If TRUE
, coordinates are used as features.
extra_args
(named list()
)
Named list of constructor arguments, required for converting task types via convert_task()
.
coordinates()
Returns coordinates of observations.
TaskRegrST$coordinates(row_ids = NULL)
row_ids
(integer()
)
Vector of rows indices as subset of task$row_ids
.
print()
Print the task.
TaskRegrST$print(...)
...
Arguments passed to the $print()
method of the superclass.
clone()
The objects of this class are cloneable with this method.
TaskRegrST$clone(deep = FALSE)
deep
Whether to make a deep clone.