Package 'bayesianrvfl'

• Title
• Fitting base rvfl
• Predict from an rvfl
• Update function

bayes_opt(
  objective,
  lower,
  upper,
  type_acq = c("ei", "ucb"),
  nb_init = 10,
  nb_iter = 25,
  kappa = 1.96,
  method = c("standard", "direct_online", "polyak_online"),
  surrogate_model = c("rvfl", "matern52", "rvfl_emcee", "rf"),
  optim_surr = c("GCV", "loglik", "cv"),
  activation_function = c("relu", "tanh", "sigmoid"),
  type_optim = c("nlminb", "DEoptim", "msnlminb", "randsearch", "none"),
  early_stopping = FALSE,
  abs_tol = 1e-07,
  rel_tol = 0.001,
  seed = 123,
  verbose = TRUE,
  show_progress = TRUE,
  ...
)

fit_rvfl(
  x,
  y,
  nb_hidden = 5,
  n_clusters = 0,
  nodes_sim = c("sobol", "halton", "unif"),
  activ = c("relu", "sigmoid", "tanh", "leakyrelu", "elu", "linear"),
  lambda = 10^seq(from = -10, to = 10, length.out = 100),
  method = c("svd", "solve", "chol"),
  compute_Sigma = FALSE,
  seed = 123
)

predict_rvfl(fit_obj, newx, ci = NULL, graph = FALSE)

update_params(
  fit_obj,
  newx,
  newy,
  re_clust = TRUE,
  method = c("direct", "polyak"),
  alpha = 0.5
)