Default Control list for spot.
This function returns the default controls for the functions spot and spotLoop.
spotControl(dimension)problem dimension, that is, the number of optimized parameters.
a list
Control is a list of the settings:
funEvalsThis is the budget of function evaluations (spot uses no more than funEvals evaluations of fun), defaults to 20.
typesVector of data type of each variable as a string, defaults "numeric" for all variables.
subsetSelectA function that selects a subset from a given set of design points. Default is selectAll.
subsetControlA list of controls passed to the control list of the subsetSelect function. See help
of the respective function for details. Default is an empty list.
designA function that creates an initial design of experiment. Functions that accept the same parameters,
and return a matrix like designLHD or designUniformRandom can be used. Default is designLHD.
designControlA list of controls passed to the control list of the design function. See help
of the respective function for details. Default is an empty list.
modelA function that builds a statistical model of the observed data. Functions that accept the same
parameters, and return a matrix like buildKriging or buildRandomForest
can be used. Default is buildKriging.
modelControlA list of controls passed to the control list of the model function.
See help of the respective function for details.Default is an empty list.
optimizerA function that is used to optimize based on model, finding the most promising
candidate solutions. Functions that accept the same parameters, and return a matrix like optimLHD
or optimDE can be used. Default is optimLHD.
optimizerControlA list of controls passed to the control list of the optimizer function.
See help of the respective function for details. Default is an empty list.
noiseBoolean, whether the objective function has noise or not. Default is non-noisy, that is, FALSE.
OCBABoolean, indicating whether Optimal Computing Budget Allocation (OCBA) should be used in case of a noisy
objective function or not. OCBA controls the number of replications for each candidate solution.
Note, that replicates should be larger than one in that case, and that the initial experimental design
(see design) should also have replicates larger one. Default is FALSE.
OCBAbudgetThe number of objective function evaluations that OCBA can distribute in each iteration. Default is 3.
replicatesThe number of times a candidate solution is initially evaluated, that is, in the initial design,
or when created by the optimizer. Default is 1.
seedFunAn initial seed for the objective function in case of noise, by default NA. The default means that no seed is set.
The user should be very careful with this setting. It is intended to generate reproducible experiments for each objective
function evaluation, e.g., when tuning non-deterministic algorithms. If the objective function uses a constant number
of random number generations, this may be undesirable. Note, that this seed is by default set prior to each evaluation. A replicated
evaluation will receive an incremented value of the seed.
Sometimes, the user may want to call external code using random numbers. To allow for that case, the user can specify an objective function (fun),
which has a second parameter seed, in addition to first parameter (matrix x). This seed can then be passed
to the external code, for random number generator initialization. See end of examples section for a demonstration.
seedSPOTThis value is used to initialize the random number generator. It ensures that experiments are reproducible. Default is 1.
duplicateIn case of a deterministic (non-noisy) objective function, this handles duplicated candidate solutions.
By default (duplicate = "EXPLORE"), duplicates are replaced by new candidate solutions, generated by random
sampling with uniform distribution. If desired, the user can set this to "STOP", which means that the optimization
stops and results are returned to the user (with a warning). This may be desirable, as duplicates can be a indicator
for convergence, or for a problem with the configuration.
In case of noise, duplicates are allowed.
plotsWhether progress should be tracked by a line plot, default is FALSE
progressWhether progress should be visualized, default is FALSE
infillCriterionA function defining an infillCriterion to be used while optimizing a model. Default: NULL. For example check infillExpectedImprovement
verbosityInteger level specifying how much output should be given by SPOT. 0 (default) ignores warnings of internal optimizers /models. 1 will show warnings and output.