Bayesian Optimization with Gaussian Prior for Hyper-Parameter

BayesianOptimization_GRNN.R

cma_out <- cmaes::cma_es(
             par = 0.5, 
             fn = function(x) grnn.optim(x, net, 4, 2019), 
             lower = 0.1, upper = 1, 
             control = list(fnscale = -1, mu = 20, lambda = 50))
#$par
#[1] 0.5766267
#$value
#[1] 0.8018076

bay_out <- rBayesianOptimization::BayesianOptimization(
             FUN = function(x) list(Score = grnn.optim(x, net, 4, 2019), Pred = 0),
             bounds = list(x = c(0.1, 1)),
             init_points = 5, n_iter = 20,
             acq = "ucb", verbose = F)
# Best Parameters Found: 
#Round = 20      x = 0.5583      Value = 0.8019