While trying to improve my neural network I wondered, whether I should increase or decrease
(default value is 6)
Training stops when any of these conditions occurs:
- "Validation performance has increased more than max_fail times since the last time it decreased (when using validation)."
which I interpret as: if validation error decreases more than 6 times -> early stopping
When the validation error increases for a specified number of iterations (net.trainParam.max_fail), the training is stopped, and the
weights and biases at the minimum of the validation error are returned.
which I interpret as: if validation error increases more than 6 times -> early stopping
So what is the purpose of the net.TrainParam.max_fail?
Second question in the same post:
When my Trainratio/Validationratio/Testratio is 70/25/5.
After how many Train-epochs is there an Validation-Epoch?
Thank you very much in advance!