OptimizerBatchGridSearch
class that implements grid search. The grid is
constructed as a Cartesian product over discretized values per parameter, see
paradox::generate_design_grid()
. The points of the grid are evaluated in a
random order.
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()
:
Parameters
resolution
integer(1)
Resolution of the grid, seeparadox::generate_design_grid()
.param_resolutions
named
integer()
Resolution per parameter, named by parameter ID, seeparadox::generate_design_grid()
.batch_size
integer(1)
Maximum number of points to try in a batch.
Progress Bars
$optimize()
supports progress bars via the package progressr
combined with a Terminator. Simply wrap the function in
progressr::with_progress()
to enable them. We recommend to use package
progress as backend; enable with progressr::handlers("progress")
.
Super classes
bbotk::Optimizer
-> bbotk::OptimizerBatch
-> OptimizerBatchGridSearch
Examples
search_space = domain = ps(x = p_dbl(lower = -1, upper = 1))
codomain = ps(y = p_dbl(tags = "minimize"))
objective_function = function(xs) {
list(y = as.numeric(xs)^2)
}
objective = ObjectiveRFun$new(
fun = objective_function,
domain = domain,
codomain = codomain)
instance = OptimInstanceBatchSingleCrit$new(
objective = objective,
search_space = search_space,
terminator = trm("evals", n_evals = 10))
optimizer = opt("grid_search")
# modifies the instance by reference
optimizer$optimize(instance)
#> x x_domain y
#> <num> <list> <num>
#> 1: 0.1111111 <list[1]> 0.01234568
# returns best scoring evaluation
instance$result
#> x x_domain y
#> <num> <list> <num>
#> 1: 0.1111111 <list[1]> 0.01234568
# allows access of data.table of full path of all evaluations
as.data.table(instance$archive$data)
#> x y x_domain timestamp batch_nr
#> <num> <num> <list> <POSc> <int>
#> 1: 1.0000000 1.00000000 <list[1]> 2024-09-11 08:25:37 1
#> 2: -0.5555556 0.30864198 <list[1]> 2024-09-11 08:25:37 2
#> 3: 0.5555556 0.30864198 <list[1]> 2024-09-11 08:25:37 3
#> 4: 0.3333333 0.11111111 <list[1]> 2024-09-11 08:25:37 4
#> 5: -0.3333333 0.11111111 <list[1]> 2024-09-11 08:25:37 5
#> 6: 0.7777778 0.60493827 <list[1]> 2024-09-11 08:25:37 6
#> 7: -0.7777778 0.60493827 <list[1]> 2024-09-11 08:25:37 7
#> 8: -1.0000000 1.00000000 <list[1]> 2024-09-11 08:25:37 8
#> 9: 0.1111111 0.01234568 <list[1]> 2024-09-11 08:25:37 9
#> 10: -0.1111111 0.01234568 <list[1]> 2024-09-11 08:25:37 10