mlr3hyperband (version 1.0.0)

mlr_optimizers_async_successive_halving: Asynchronous Hyperparameter Optimization with Successive Halving

Description

OptimizerAsyncSuccessiveHalving class that implements the Asynchronous Successive Halving Algorithm (ASHA). This class implements the asynchronous version of OptimizerBatchSuccessiveHalving.

Dictionary

This bbotk::Optimizer can be instantiated via the dictionary bbotk::mlr_optimizers or with the associated sugar function bbotk::opt():

mlr_optimizers$get("async_successive_halving")
opt("async_successive_halving")

Parameters

eta

numeric(1)
With every stage, the budget is increased by a factor of eta and only the best 1 / eta configurations are promoted to the next stage. Non-integer values are supported, but eta is not allowed to be less or equal to 1.

sampler

paradox::Sampler
Object defining how the samples of the parameter space should be drawn. The default is uniform sampling.

Archive

The bbotk::Archive holds the following additional columns that are specific to SHA:

• stage (integer(1))
  Stage index. Starts counting at 0.

• asha_id (character(1))
  Unique identifier for each configuration across stages.

Custom Sampler

Hyperband supports custom paradox::Sampler object for initial configurations in each bracket. A custom sampler may look like this (the full example is given in the examples section):

# - beta distribution with alpha = 2 and beta = 5
# - categorical distribution with custom probabilities
sampler = SamplerJointIndep$new(list(
  Sampler1DRfun$new(params[[2]], function(n) rbeta(n, 2, 5)),
  Sampler1DCateg$new(params[[3]], prob = c(0.2, 0.3, 0.5))
))

Super classes

bbotk::Optimizer -> bbotk::OptimizerAsync -> OptimizerAsyncSuccessiveHalving

Methods

Public methods

• OptimizerAsyncSuccessiveHalving$new()

• OptimizerAsyncSuccessiveHalving$optimize()

• OptimizerAsyncSuccessiveHalving$clone()

Inherited methods

• bbotk::Optimizer$format()
• bbotk::Optimizer$help()
• bbotk::Optimizer$print()

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Method new()

Creates a new instance of this R6 class.

Usage

OptimizerAsyncSuccessiveHalving$new()

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Method optimize()

Performs the optimization on a bbotk::OptimInstanceAsyncSingleCrit or bbotk::OptimInstanceAsyncMultiCrit until termination. The single evaluations will be written into the bbotk::ArchiveAsync. The result will be written into the instance object.

Usage

OptimizerAsyncSuccessiveHalving$optimize(inst)

Arguments

inst

(bbotk::OptimInstanceAsyncSingleCrit | bbotk::OptimInstanceAsyncMultiCrit).

Returns

data.table::data.table()

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Method clone()

The objects of this class are cloneable with this method.

Usage

OptimizerAsyncSuccessiveHalving$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.