NEWS.md

In pday2/mlrMBO_mP: Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions

mlrMBO 1.1.4

• plot.OptState() now supports multiple categorical variables.
• crit.aei works with wrapped learners.
• Documentation fixes
• mbo() can be called without control object.
• Bugix: MOIMBO works with integers

mlrMBO 1.1.3

• Bugfix: plot(opt.state) now also works for Param Sets with transformations.
• Bugfix: Infill optimization with CMAES now supports restarts.

mlrMBO 1.1.2

• Adaptive infill criterions. Infill criterions now have to support an progress argument. Termination criterions now can supply a progress return value.
• Fix for parEGO + EI (Issue #407)
• save.on.disk now can take arbitrary numeric vectors to specify iterations, when to save on disk.
• Spelling mistakes for infill criterions will now be cought. (Issue #417)

mlrMBO 1.1.1

• makeMBOControl() has on.surrogate.error argument which enables random proposals if the surrogate model fails.
• With initSMBO(), updateSMBO() and finalizeSMBO() it is now possible to do a human-in-the-loop MBO.
• The result now contains the final.opt.state.
• Plot method for OptState objects.

mlrMBO 1.1.0

• Fixed bug in focus search that affected discrete search spaces.
• Numerics will be auto converted to integers where integers are expected.
• Package can now be cited with citation("mlrMBO").

mlrMBO 1.0.0

• Initial CRAN release

pday2/mlrMBO_mP documentation built on July 21, 2020, 12:16 a.m.