Inverse-distance-weighted active-learning acquisition function using an ALDistance.
The basic score is an IDW-weighted squared residual plus the IDEAL
exploration term. With omega > 0, $fit_pool() precomputes the IDEAL
pool-density multiplier on the fitted candidate pool. When fitted with
xdt = NULL, the population-case density multiplier is set to 1.
Creates a new distance-aware IDEAL acquisition function.
Clears precomputed density values.
Arguments
- surrogate
(
NULL| mlr3mbo::SurrogateLearner)
Surrogate used for mean predictions.- al_distance
(ALDistance |
NULL)
Distance used for the IDW geometry.- delta
(
numeric(1))
Exploration weight.- omega
(
numeric(1))
Density multiplier weight.- tolerance_equality
(
numeric(1))
Squared-distance tolerance for the exact-match branch.
See also
Other Acquisition Function:
AcqFunctionDist,
AcqFunctionDistGSx,
AcqFunctionDistIGS,
AcqFunctionGSy,
SurrogateNull