bayesian-optimization
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Why is `greater_is_better` set to `True`?
In gp.py (when finding the next sample):
next_sample = sample_next_hyperparameter(expected_improvement, model, yp, greater_is_better=True, bounds=bounds, n_restarts=100)
Here greater_is_better
is True means that its trying to maximize the loss function instead of minimizing it.