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.
Super classes
mlr3::Task -> mlr3::TaskUnsupervised -> TaskDens
Methods
Inherited methods
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$levels()mlr3::Task$materialize_view()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()
Method new()
Creates a new instance of this R6 class.
Usage
TaskDens$new(id, backend, label = NA_character_)Arguments
id(
character(1))
Identifier for the new instance.backend(mlr3::DataBackend)
Either a DataBackend, a matrix-like object, or a numeric vector. If weights are used then two columns expected, otherwise one column. The weight column must be clearly specified (via[Task]$col_roles) or the learners will break.label(
character(1))
Label for the new instance.