I'm running a grid search, in order to fine-tune a NN hyper parameters. the question is: the MAE values I get from the trainings are too close. since I have the statistical attributes of the target values, is there a way to somehow come up with a starting value for MAE, where the worst regression can achieve.
I think the question is not clear. the value I'm looking for, is analogous to a probability for classification problems. (example: an neural network which is supposed to classify the inputs into 8 possible classes, will have accuracy of 0.125 just by random classification of inputs. so a 12.5% accuracy is the measure for such classifier) now, I have the Mean, and StdDev (and other stats if need be) of the target values of my samples. how can I calculate a measure to judge my MAE (and not by comparing different MAE values from different trainings)?