SamplerHierarchical: SamplerHierarchical Class

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

SamplerHierarchical Class

Description

Hierarchical sampling for arbitrary param sets with dependencies, where the user specifies 1D samplers per param. Dependencies are topologically sorted, parameters are then sampled in topological order, and if dependencies do not hold, values are set to NA in the resulting data.table.

Super class

paradox::Sampler -> SamplerHierarchical

Public fields

samplers

(list())
List of Sampler1D objects that gives a Sampler for each dimension in the param_set.

Methods

Public methods

• SamplerHierarchical$new()

• SamplerHierarchical$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

SamplerHierarchical$new(param_set, samplers)

Arguments

param_set

(ParamSet)
The ParamSet to associated with this SamplerHierarchical.

samplers

(list())
List of Sampler1D objects that gives a Sampler for each dimension in the param_set.

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Method clone()

The objects of this class are cloneable with this method.

Usage

SamplerHierarchical$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other Sampler: Sampler1DCateg, Sampler1DNormal, Sampler1DRfun, Sampler1DUnif, Sampler1D, SamplerJointIndep, SamplerUnif, Sampler

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