The ArchiveBest stores no data but records the best scoring evaluation
passed to $add_evals(). The Archive API is fully implemented but many
parameters are ignored and some methods do nothing. The archive still works
with TerminatorClockTime, TerminatorEvals, TerminatorNone and
TerminatorEvals.
Super class
bbotk::Archive -> ArchiveBest
Active bindings
n_evals(
integer(1))
Number of evaluations stored in the archive.n_batch(
integer(1))
Number of batches stored in the archive.
Methods
Method new()
Creates a new instance of this R6 class.
Usage
ArchiveBest$new(search_space, codomain, check_values = FALSE)Arguments
search_space(paradox::ParamSet)
Specifies the search space for the Optimizer. The paradox::ParamSet describes either a subset of thedomainof the Objective or it describes a set of parameters together with atrafofunction that transforms values from the search space to values of the domain. Depending on the context, this value defaults to the domain of the objective.codomain(paradox::ParamSet)
Specifies codomain of function. Most importantly the tags of each output "Parameter" define whether it should be minimized or maximized. The default is to minimize each component.check_values(
logical(1))
ignored.
Method add_evals()
Stores the best result in ydt.
Arguments
xdt(
data.table::data.table())
Set of untransformed points / points from the search space. One point per row, e.g.data.table(x1 = c(1, 3), x2 = c(2, 4)). Column names have to match ids of thesearch_space. However,xdtcan contain additional columns.xss_trafoed(
list())
Transformed point(s) in the domain space.ydt(
data.table::data.table())
Optimal outcome.
Method best()
Returns the best scoring evaluation. For single-crit optimization, the solution that minimizes / maximizes the objective function. For multi-crit optimization, the Pareto set / front.
Arguments
m(
integer())
ignored.