inst/examples/ex_2d_numeric_multipoint.R

In berndbischl/mlrMBO: Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions

#####################################################
###
### optimizing branin in 2D with multipoint proposal #####
###
#####################################################
\dontrun{
library(mlrMBO)
library(ggplot2)
set.seed(2)
configureMlr(show.learner.output = FALSE)

obj.fun = makeBraninFunction()

ctrl = makeMBOControl(propose.points = 5L)
ctrl = setMBOControlInfill(ctrl, crit = makeMBOInfillCritMeanResponse())
ctrl = setMBOControlTermination(ctrl, iters = 10L)
ctrl = setMBOControlMultiPoint(ctrl,
  method = "moimbo",
  moimbo.objective = "ei.dist",
  moimbo.dist = "nearest.neighbor",
  moimbo.maxit = 200L
)

lrn = makeLearner("regr.km", predict.type = "se")
design = generateDesign(10L, getParamSet(obj.fun), fun = lhs::maximinLHS)

run = exampleRun(obj.fun, design = design, learner = lrn, control = ctrl,
	points.per.dim = 50L, show.info = TRUE)

print(run)

plotExampleRun(run, gg.objects = list(theme_bw()))
}