Optimization via Random Search — mlr_optimizers_random

OptimizerBatchRandomSearch 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.

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.

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.

Progress Bars

$optimize() supports progress bars via the package progressr combined with a Terminator. Simply wrap the function in progressr::with_progress() to enable them. We recommend to use package progress as backend; enable with progressr::handlers("progress").

Super classes

Optimizer -> OptimizerBatch -> OptimizerBatchRandomSearch

Methods

Inherited methods

`OptimizerBatchRandomSearch$new()`

Creates a new instance of this R6 class.

Usage

OptimizerBatchRandomSearch$new()

`OptimizerBatchRandomSearch$clone()`

The objects of this class are cloneable with this method.

Usage

OptimizerBatchRandomSearch$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

# define the objective function
fun = function(xs) {
  list(y = - (xs[[1]] - 2)^2 - (xs[[2]] + 3)^2 + 10)
}

# set domain
domain = ps(
  x1 = p_dbl(-10, 10),
  x2 = p_dbl(-5, 5)
)

# set codomain
codomain = ps(
  y = p_dbl(tags = "maximize")
)

# create objective
objective = ObjectiveRFun$new(
  fun = fun,
  domain = domain,
  codomain = codomain,
  properties = "deterministic"
)

# initialize instance
instance = oi(
  objective = objective,
  terminator = trm("evals", n_evals = 20)
)

# load optimizer
optimizer = opt("random_search", batch_size = 10)

# trigger optimization
optimizer$optimize(instance)
#>          x1         x2  x_domain       y
#>       <num>      <num>    <list>   <num>
#> 1: 1.566668 -0.2343097 <list[2]> 2.16318

# all evaluated configurations
instance$archive
#> 
#> ── <ArchiveBatch> - Data Table Storage ─────────────────────────────────────────
#>        x1     x2     y           timestamp batch_nr x_domain_x1 x_domain_x2
#>     <num>  <num> <num>              <POSc>    <int>       <num>       <num>
#>  1:  -7.5 -3.411   -80 2026-08-07 14:44:09        1        -7.5      -3.411
#>  2:  -4.6 -1.715   -35 2026-08-07 14:44:09        1        -4.6      -1.715
#>  3:  -8.2  2.961  -129 2026-08-07 14:44:09        1        -8.2       2.961
#>  4:   6.8 -1.387   -16 2026-08-07 14:44:09        1         6.8      -1.387
#>  5:  -5.0  3.733   -85 2026-08-07 14:44:09        1        -5.0       3.733
#>  6:  -1.6  4.537   -60 2026-08-07 14:44:09        1        -1.6       4.537
#>  7:  -8.4 -4.783  -102 2026-08-07 14:44:09        1        -8.4      -4.783
#>  8:  -9.7  4.776  -186 2026-08-07 14:44:09        1        -9.7       4.776
#>  9:  -0.6  0.694   -11 2026-08-07 14:44:09        1        -0.6       0.694
#> 10:   7.4  4.774   -79 2026-08-07 14:44:09        1         7.4       4.774
#> 11:   6.9 -0.008   -23 2026-08-07 14:44:09        2         6.9      -0.008
#> 12:   1.6 -0.234     2 2026-08-07 14:44:09        2         1.6      -0.234
#> 13:   8.0 -1.193   -30 2026-08-07 14:44:09        2         8.0      -1.193
#> 14:  -7.5  0.202   -91 2026-08-07 14:44:09        2        -7.5       0.202
#> 15:  -9.1 -0.207  -121 2026-08-07 14:44:09        2        -9.1      -0.207
#> 16:  -3.9  2.411   -54 2026-08-07 14:44:09        2        -3.9       2.411
#> 17:  -6.9 -3.768   -70 2026-08-07 14:44:09        2        -6.9      -3.768
#> 18:   9.3 -3.079   -44 2026-08-07 14:44:09        2         9.3      -3.079
#> 19:  -4.4 -2.351   -31 2026-08-07 14:44:09        2        -4.4      -2.351
#> 20:   1.7  1.904   -14 2026-08-07 14:44:09        2         1.7       1.904
#>        x1     x2     y           timestamp batch_nr x_domain_x1 x_domain_x2
#>     <num>  <num> <num>              <POSc>    <int>       <num>       <num>

# best performing configuration
instance$result
#>          x1         x2  x_domain       y
#>       <num>      <num>    <list>   <num>
#> 1: 1.566668 -0.2343097 <list[2]> 2.16318