What stopping metric to chose to optimize 'sensitivity' for a GBM in H2O?
One solution to make the recall more important whitout getting to the problem mentionned by @Jurgy is to use $F_\beta$, a modified version of $F_1$ where recall is considered $\beta$ time more important. As seen here : https://en.wikipedia.org/wiki/F1_score, $F_\beta$ can be formulated both in terms of recall/precision, and in term of type I /type II error. You then need to select a $\beta$ based on how much recall is more important to you... this can be done by considerations on the costs of type I vs the cost of type II errors.