Hi,
I used the H2O Gradient Boosting Machine Learner in one of my workflows and noticed that for a binomial classification task the cutoff between the positive and negative value is not at the standard 0.5.
This behaviour can also be noticed in the example workflow 05_H2O_Scoring on the example server. There are 3 classifications whose probabilities for Cluster_1 is above 0.5 but the prediction is still Cluster_0.
Are the probablities correct so that I just could overwrite the predicton based on the probability?
Cheers