How can I specify a validation dataset for H2o Deep Learning model in RapidMiner
I'm using the Deep Learning model of the H2o framework available in RapidMiner.
To perform my analyses I don't see how to control the data used for validation step at the end of each epoch.
For example, with Keras you have to specify the training set rate, and that part of your data are used for the validation.
With Pytorch, we provide the training, the validation and the test set.
How can I do with RapidMiner?
I am also wondering how to see the loss curve in order to evaluate if the model overfit with respect to the number of epochs.
Do you have an idea for any of these questions ?