Cassini Classification Task Generator
Source:R/TaskGeneratorCassini.R
mlr_task_generators_cassini.Rd
A TaskGenerator for the cassini task in mlbench::mlbench.cassini()
.
Dictionary
This TaskGenerator can be instantiated via the dictionary mlr_task_generators or with the associated sugar function tgen()
:
Parameters
Id | Type | Default | Range |
relsize1 | integer | 2 | \([1, \infty)\) |
relsize2 | integer | 2 | \([1, \infty)\) |
relsize3 | integer | 1 | \([1, \infty)\) |
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_2dnormals
,
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
-> TaskGeneratorCassini
Examples
generator = tgen("cassini")
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/ 3 levels "A","B","C": 1 1 1 1 1 1 1 1 1 1 ...
#> $ x1: num -0.437 -0.252 -1.01 -0.849 0.846 ...
#> $ x2: num -1.78 -1.02 -1.37 -1.09 -1.36 ...
#> - attr(*, ".internal.selfref")=<externalptr>