TaskDens {mlr3proba}R Documentation

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

Inherited methods

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

task = TaskDens$new("precip", backend = precip)
task$task_type
[Package mlr3proba version 0.4.2 Index]