Objective interface where user can pass an R function that works on an data.table().
Super class
bbotk::Objective -> ObjectiveRFunDt
Methods
Method new()
Creates a new instance of this R6 class.
Usage
ObjectiveRFunDt$new(
fun,
domain,
codomain = NULL,
id = "function",
properties = character(),
constants = ps(),
check_values = TRUE
)Arguments
fun(
function)
R function that encodes objective and expects andata.table()as input whereas each point is represented by one row.domain(paradox::ParamSet)
Specifies domain of function. The paradox::ParamSet should describe all possible input parameters of the objective function. This includes theirid, their types and the possible range.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.id(
character(1)).properties(
character()).constants(paradox::ParamSet)
Changeable constants or parameters that are not subject to tuning can be stored and accessed here.check_values(
logical(1))
Should points before the evaluation and the results be checked for validity?
Method eval_many()
Evaluates multiple input values received as a list, converted to a data.table() on the
objective function. Missing columns in xss are filled with NAs in xdt.
Arguments
xss(
list())
A list of lists that contains multiple x values, e.g.list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4)).
Returns
data.table::data.table() that contains one y-column for single-criteria functions
and multiple y-columns for multi-criteria functions, e.g.
data.table(y = 1:2) or data.table(y1 = 1:2, y2 = 3:4).
Method eval_dt()
Evaluates multiple input values on the objective function supplied by the user.
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.