Chapter 14 Iterative search

Learning objectives:

• Use tune::tune_bayes() to optimize model parameters using Bayesian optimization.
  • Describe how a Gaussian process model can be applied to parameter optimization.
  • Explain how acquisition functions can be expressed as a trade-off between exploration and exploitation.
  • Describe expected improvement, the default acquisition function used by {tidymodels}.
• Use finetune::tune_sim_anneal() to optimize model parameters using Simulated annealing.
  • Describe simulated annealing search.