Sampler1DCateg: Sampler1DCateg Class

In mlr-org/phng: Define and Work with Parameter Spaces for Complex Algorithms

Sampler1DCateg Class

Description

Sampling from a discrete distribution, for a ParamSet containing a single p_fct() or p_lgl().

Super classes

paradox::Sampler -> paradox::Sampler1D -> Sampler1DCateg

Public fields

prob

(numeric() | NULL)
Numeric vector of param$nlevels probabilities.

Methods

Public methods

• Sampler1DCateg$new()

• Sampler1DCateg$clone()

Inherited methods

• paradox::Sampler$format()
• paradox::Sampler$print()
• paradox::Sampler$sample()

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Method new()

Creates a new instance of this R6 class.

Usage

Sampler1DCateg$new(param, prob = NULL)

Arguments

param

(ParamSet)
Domain / support of the distribution we want to sample from. Must be one-dimensional.

prob

(numeric() | NULL)
Numeric vector of param$nlevels probabilities, which is uniform by default.

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Method clone()

The objects of this class are cloneable with this method.

Usage

Sampler1DCateg$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other Sampler: Sampler1DNormal, Sampler1DRfun, Sampler1DUnif, Sampler1D, SamplerHierarchical, SamplerJointIndep, SamplerUnif, Sampler

mlr-org/phng documentation built on April 1, 2024, 2:06 a.m.