mlr3proba (version 0.2.6)

TaskDens: Density Task

Description

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

Public methods

• TaskDens$new()

• TaskDens$clone()

• 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$print()

• mlr3::Task$rbind()

• mlr3::Task$rename()

• mlr3::Task$select()

• mlr3::Task$set_col_roles()

• mlr3::Task$set_row_roles()

Method new()

Creates a new instance of this R6 class.

Usage

TaskDens$new(id, backend)

Arguments

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.

Method clone()

The objects of this class are cloneable with this method.

Usage

TaskDens$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other Task: TaskSurv

Examples

# NOT RUN {
task = TaskDens$new("precip", backend = precip)
task$task_type
# }