boax.acquisitions.log_expected_improvement#
- boax.acquisitions.log_expected_improvement(bounds, improvement_factor=1.0, num_raw_samples=512, num_restarts=10)#
The Log Expected Improvement acquisition function.
Logarithm of the expected improvement over the best function value observed so far.
LogEI(x) = log(E(max(f(x) - best, 0))),
where the expectation is taken over the value of stochastic function f at x.
References
Ament, Sebastian, et al. “Unexpected improvements to expected improvement for bayesian optimization.” arXiv preprint arXiv:2310.20708 (2023).
Example
>>> acqf = log_expected_improvement(0.2, model) >>> log_ei = acqf(index_points)
- Parameters:
best – The best function value observed so far.
model – The surrogate model.
- Return type:
- Returns:
The corresponding Acquisition.