Smiley Classification Task Generator

A TaskGenerator for the smiley task in mlbench::mlbench.smiley().

Dictionary

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

mlr_task_generators$get("smiley")
tgen("smiley")

Parameters

Id	Type	Default	Range
sd1	numeric	-	\([0, \infty)\)
sd2	numeric	-	\([0, \infty)\)

See also

• Dictionary of TaskGenerators: mlr_task_generators

• 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_cassini, mlr_task_generators_circle, mlr_task_generators_friedman1, mlr_task_generators_moons, mlr_task_generators_peak, mlr_task_generators_simplex, mlr_task_generators_spirals, mlr_task_generators_xor

Super class

mlr3::TaskGenerator -> TaskGeneratorSmiley

Methods

Public methods

• TaskGeneratorSmiley$new()

• TaskGeneratorSmiley$plot()

• TaskGeneratorSmiley$clone()

Inherited methods

• mlr3::TaskGenerator$format()
• mlr3::TaskGenerator$generate()
• mlr3::TaskGenerator$print()

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Method new()

Creates a new instance of this R6 class.

Usage

TaskGeneratorSmiley$new()

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Method plot()

Creates a simple plot of generated data.

Usage

TaskGeneratorSmiley$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().

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Method clone()

The objects of this class are cloneable with this method.

Usage

TaskGeneratorSmiley$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

generator = tgen("smiley")
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/ 4 levels "A","B","C","D": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ x1: num  -0.811 -0.786 -0.891 -0.764 -0.759 ...
#>  $ x2: num  1.074 0.873 0.984 0.963 1.12 ...
#>  - attr(*, ".internal.selfref")=<externalptr>