getLocalOptimums: Get Local Optimums of acq From a bayesOpt Object

In ParBayesianOptimization: Parallel Bayesian Optimization of Hyperparameters

Get Local Optimums of acq From a bayesOpt Object

Description

Returns all local optimums of the acquisition function, no matter the utility.

Usage

getLocalOptimums(
  optObj,
  bounds = optObj$bounds,
  acq = optObj$optPars$acq,
  kappa = optObj$optPars$kappa,
  eps = optObj$optPars$eps,
  convThresh = optObj$optPars$convThresh,
  gsPoints = optObj$optPars$gsPoints,
  parallel = FALSE,
  verbose = 1
)

Arguments

optObj	an object of class bayesOpt. The following parameters are all defaulted to the options provided in this object, but can be manually specified.
bounds	Same as in bayesOpt()
acq	Same as in bayesOpt()
kappa	Same as in bayesOpt()
eps	Same as in bayesOpt()
convThresh	Same as in bayesOpt()
gsPoints	Same as in bayesOpt()
parallel	Same as in bayesOpt()
verbose	Should warnings be shown before results are returned prematurely?

Details

gsPoints points in the parameter space are randomly initialized, and the L-BFGS-B method is used to find the closest local optimum to each point. dbscan is then used to cluster points together which converged to the same optimum - only unique optimums are returned.

Value

A data table of local optimums, including the utility (gpUtility), the utility relative to the max utility (relUtility), and the steps taken in the L-BFGS-B method (gradCount).

Examples

scoringFunction <- function(x) {
  a <- exp(-(2-x)^2)*1.5
  b <- exp(-(4-x)^2)*2
  c <- exp(-(6-x)^2)*1
  return(list(Score = a+b+c))
}

bounds <- list(x = c(0,8))

Results <- bayesOpt(
    FUN = scoringFunction
  , bounds = bounds
  , initPoints = 3
  , iters.n = 2
  , gsPoints = 10
)
print(getLocalOptimums(Results))

ParBayesianOptimization documentation built on Oct. 18, 2022, 5:07 p.m.