rebalancing

I would like to build a GBM model with H2O. My data set is imbalanced, so I am using the balance_classes parameter. For grid search (parameter tuning) I would like to use 5-fold cross validation. I am wondering how H2O deals with class balancing in that case. Will only the training folds be rebalanced? I want to be sure the test-fold is not rebalanced. Thank you. In class imbalance settings, artificially balancing the test/validation set does not make any sense: these sets must remain realistic , i.e. you want to test your classifier performance in the real world setting, where, say, the

While looking into the resource balancer and dynamic load metrics on Service Fabric, we ran into some questions (Running devbox SDK GA 2.0.135). In the Service Fabric Explorer (the portal and the standalone application) we can see that the balancing is ran very often, most of the time it is done almost instantly and this happens every second. While looking at the Load Metric Information on the nodes or partitions it is not updating the values as we report load. We send a dynamic load report based on our interaction (a HTTP request to a service), increasing the reported load data of a single