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.