Changelog • mlr3mbo

mlr3mbo 0.2.1

docs: updated some references in vignette.
refactor: minor clean up of the internal structure of all loop functions.
perf: default initial design constructed based on a Sobol sequence in all loop functions.
refactor: no longer depend on mlr3tuning but import instead.
refactor: srlrn sugar function now can construct both a SurrogateLearner and SurrogateLearnerCollection; dropped srlrnc.
feat: added AcqFunctionSD, AcqFunctionEHVI and AcqFunctionEHVIGH, introduced bayesopt_emo loop function.
feat: AcqFunctions now include a $packages field stating required packages which are checked for whether their namespace can be loaded prior to optimization.
fix: fixed bug in fix_xdt_missing() helper function.
BREAKING CHANGE: renaming default_loopfun -> default_loop_function, default_acqfun -> default_acqfunction, default_acqopt -> default_acqoptimizer.
BREAKING CHANGE: result_functions now replaced by ResultAssigners.
BREAKING CHANGE: renamed $model field of all Surrogate classes to $learner.
BREAKING CHANGE: For all Surrogate and AcquisitionFunction classes fields *_cols renamed to cols_* (e.g., x_cols to cols_x).

CRAN release: 2023-03-02

refactor: adapt to mlr3tuning 0.18.0.
feat: Acquisition functions now assert whether surrogates match their required predict type.
fix: Unloading mlr3mbo removes optimizers and tuners from the dictionaries.
docs: faster examples.
feat: characters in surrogate regression tasks are no longer automatically converted to factors. default_surrogate now respects this and gained an appropriate pipeline step.
feat: AcqFunctionAEI added.
docs: fix of docs, README and bibentries.

CRAN release: 2022-11-18