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Related Questions
- How do Gaussian processes and random forests compare in terms of function approximations and uncertainty estimates?
- What are the key differences in convergence speed and exploration-exploitation trade-offs between the two methods?
- How do the choice of kernel and hyperparameters in Gaussian processes affect the search efficiency in Bayesian optimization?
- Can you provide an example of a problem where random forests outperform Gaussian processes in Bayesian optimization?
- How do Gaussian processes handle high-dimensional feature spaces, and are there any limitations or pitfalls to be aware of?
- What are some scenarios where the interpretability of random forests is an advantage over Gaussian processes?
- Can you compare the computational costs of implementing and training Gaussian processes versus random forests in Bayesian optimization?
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