gp_helpers.md
In tune: Tidy Tuning Tools

GP fit - svm - failure

Code
  svm_gp <- tune:::fit_gp(collect_metrics(svm_results), pset = svm_set, metric = "accuracy",
  control = control_bayes(verbose = TRUE))

Code
  svm_scores <- tune:::pred_gp(svm_gp, pset = svm_set, size = 20, current = curr,
    control = control_bayes(verbose_iter = TRUE))
Message
  i Generating a candidate as far away from existing points as possible.

GP scoring with failed model

Code
  svm_gp <- tune:::fit_gp(collect_metrics(svm_results), pset = svm_set, metric = "accuracy",
  control = ctrl)
Message
  (x) GP has a LOO R² of -6.1% and is unreliable.
  v Gaussian process model failed

Code
  svm_scores <- tune:::pred_gp(svm_gp, pset = svm_set, size = 20, current = curr,
    control = ctrl)
Message
  i Generating a candidate as far away from existing points as possible.

pick_candidate() emits uncertainty sample message when verbose

Code
  set.seed(1)
  res <- tune:::pick_candidate(results, info, ctrl)
Message
  i Uncertainty sample

GP fit - knn

Code
  set.seed(1)
  knn_scores <- tune:::pred_gp(knn_gp, pset = knn_set, size = 20, current = mutate(
    knn_mtr, .iter = 0), control = control_bayes())