design = train + validate
train : Weight Estimation
validate: Not directly involved in weight estimation. Protects ability to generalize to nontraining data. Stops training when the nontraining val subset error rate increases CONTINUOUSLY for more than 6 (default) epochs.
val subset error rate is therefore SLIGHTLY biased.
test subset error rate is COMPLETELY unbiased
default division ratio = 0.7/0.15/0.15
If val stopping occurs, take a look at the error rate curves and you will see why training was stopped.
OBVIOUSLY, the most unbiased approach for constant timestep timeseries prediction is to use DIVIDEBLOCK data division with the validation subset in the middle.
Hope this helps
Thank you for formally accepting my answer