All the fitness curve of training is good for is stopping the iterations. The only only thing that tells you "fitness" is the forward test equity curve. To automate the process, I would like to be able to train in walkforward test increments, say quarters. Having generated rules for quarter 1 and generated an equity curve, it would use them in the next quarter to generate an out-of-sample equity curve for quarter 2, then use quarter 2 to train and generate a training set equity curve, adding rules to those from quarter 1. An equity curve for quarter 3 would be run, then more training with quarter 3. And so on. This way, you could compare equity curves from the walkforward segments with an equity curve from the training data. All curve fitting would be apparent as it happens.