2D Normals Classification Task Generator

Source: R/TaskGenerator2DNormals.R

A TaskGenerator for the 2d normals task in mlbench::mlbench.2dnormals().

Dictionary

This TaskGenerator can be instantiated via the dictionary mlr_task_generators or with the associated sugar function tgen():

mlr_task_generators$get("2dnormals")
tgen("2dnormals")

See also

Dictionary of TaskGenerators: mlr_task_generators

as.data.table(mlr_resamplings) for a complete table of all (also dynamically created) TaskGenerator implementations.

Other TaskGenerator: TaskGenerator, mlr_task_generators_cassini, mlr_task_generators_circle, mlr_task_generators_friedman1, mlr_task_generators_moons, mlr_task_generators_simplex, mlr_task_generators_smiley, mlr_task_generators_spirals, mlr_task_generators_xor, mlr_task_generators

Super class

mlr3::TaskGenerator -> TaskGenerator2DNormals

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

TaskGenerator2DNormals$new()

Method plot()

Creates a simple plot of generated data.

Usage

TaskGenerator2DNormals$plot(n = 200L, pch = 19L, ...)

Arguments

n

(integer(1))
Number of samples to draw for the plot. Default is 200.

pch

(integer(1))
Point char. Passed to plot().

...

(any)
Additional arguments passed to plot().

Method clone()

The objects of this class are cloneable with this method.

Usage

TaskGenerator2DNormals$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

generator = tgen("2dnormals")
plot(generator, n = 200)


task = generator$generate(200)
str(task$data())

#> Classes ‘data.table’ and 'data.frame':	200 obs. of  3 variables:
#>  $ y : Factor w/ 2 levels "A","B": 2 1 1 2 2 1 1 2 1 2 ...
#>  $ x1: num  -3.25 0.511 -0.119 -0.569 -1.829 ...
#>  $ x2: num  -2.548 0.118 0.395 0.378 -1.599 ...
#>  - attr(*, ".internal.selfref")=<externalptr>