mlr_optimizers_random_search {bbotk}R Documentation

Optimization via Random Search

Description

OptimizerRandomSearch class that implements a simple Random Search.

In order to support general termination criteria and parallelization, we evaluate points in a batch-fashion of size batch_size. Larger batches mean we can parallelize more, smaller batches imply a more fine-grained checking of termination criteria.

Dictionary

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

mlr_optimizers$get("random_search")
opt("random_search")

Parameters

batch_size

integer(1)
Maximum number of points to try in a batch.

Super class

bbotk::Optimizer -> OptimizerRandomSearch

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
OptimizerRandomSearch$new()

Method clone()

The objects of this class are cloneable with this method.

Usage
OptimizerRandomSearch$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Source

Bergstra J, Bengio Y (2012). “Random Search for Hyper-Parameter Optimization.” Journal of Machine Learning Research, 13(10), 281–305. https://jmlr.csail.mit.edu/papers/v13/bergstra12a.html.

Examples

library(paradox)

domain = ParamSet$new(list(ParamDbl$new("x", lower = -1, upper = 1)))

search_space = ParamSet$new(list(ParamDbl$new("x", lower = -1, upper = 1)))

codomain = ParamSet$new(list(ParamDbl$new("y", tags = "minimize")))

objective_function = function(xs) {
  list(y = as.numeric(xs)^2)
}

objective = ObjectiveRFun$new(fun = objective_function,
                              domain = domain,
                              codomain = codomain)
terminator = trm("evals", n_evals = 10)
instance = OptimInstanceSingleCrit$new(objective = objective,
                             search_space = search_space,
                             terminator = terminator)

optimizer = opt("random_search")

# Modifies the instance by reference
optimizer$optimize(instance)

# Returns best scoring evaluation
instance$result

# Allows access of data.table of full path of all evaluations
instance$archive$data()
[Package bbotk version 0.2.2 Index]