2D Normals Classification Task Generator
Source:R/TaskGenerator2DNormals.R
mlr_task_generators_2dnormals.Rd
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()
:
Parameters
Id | Type | Default | Range |
cl | integer | - | \([2, \infty)\) |
r | numeric | - | \([1, \infty)\) |
sd | numeric | - | \([0, \infty)\) |
See also
as.data.table(mlr_task_generators)
for a table of available TaskGenerators in the running session (depending on the loaded packages).Extension packages for additional task types:
mlr3proba for probabilistic supervised regression and survival analysis.
mlr3cluster for unsupervised clustering.
Other TaskGenerator:
TaskGenerator
,
mlr_task_generators
,
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
Super class
mlr3::TaskGenerator
-> TaskGenerator2DNormals
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 2 2 2 2 1 2 2 1 ...
#> $ x1: num -1.319 2.38 -1.27 0.456 0.289 ...
#> $ x2: num -0.0177 1.2888 -2.629 -1.1528 -0.6506 ...
#> - attr(*, ".internal.selfref")=<externalptr>