Note: Bayesian optimization for hyperparameter search
Intermediate classical-mlevaluationhyperparameter-tuninggaussian-processes
Implement:
def expected_improvement(mean, std, best_so_far, xi=0.01) -> np.ndarray: ...
def propose_next_point(input_train, targets_train, candidates, length_scale, variance, noise, xi=0.01) -> int: ...
- Reuse
05-gaussian-processes's gp_predict.