The decision threshold is the probability above which the positive class is predicted; it is 0.5 by default but can be changed. Lowering it captures more positives (better recall) at the cost of more false positives; raising it does the opposite. It is chosen according to the cost of errors.
Example
pred = (proba >= 0.3).astype(int)