TaskDens | R Documentation |
This task specializes TaskUnsupervised for density estimation problems.
The data in backend
should be a numeric vector or a one column matrix-like object.
The task_type
is set to "density"
.
Predefined tasks are stored in the dictionary mlr_tasks.
mlr3::Task
-> mlr3::TaskUnsupervised
-> TaskDens
mlr3::Task$add_strata()
mlr3::Task$cbind()
mlr3::Task$data()
mlr3::Task$divide()
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$print()
mlr3::Task$rbind()
mlr3::Task$rename()
mlr3::Task$select()
mlr3::Task$set_col_roles()
mlr3::Task$set_levels()
mlr3::Task$set_row_roles()
new()
Creates a new instance of this R6 class.
TaskDens$new(id, backend, label = NA_character_)
id
(character(1)
)
Identifier for the new instance.
backend
(DataBackend)
Either a DataBackend, a matrix-like object, or a numeric vector.
If weights are used then two columns expected, otherwise one column. The weight column
must be clearly specified (via [Task]$col_roles
) or the learners will break.
label
(character(1)
)
Label for the new instance.
clone()
The objects of this class are cloneable with this method.
TaskDens$clone(deep = FALSE)
deep
Whether to make a deep clone.
Other Task:
TaskSurv
,
mlr_tasks_actg
,
mlr_tasks_faithful
,
mlr_tasks_gbcs
,
mlr_tasks_gbsg
,
mlr_tasks_grace
,
mlr_tasks_lung
,
mlr_tasks_mgus
,
mlr_tasks_pbc
,
mlr_tasks_precip
,
mlr_tasks_rats
,
mlr_tasks_veteran
,
mlr_tasks_whas
task = TaskDens$new("precip", backend = precip)
task$task_type
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