What are the performance measures in the neural networks field?
Typical predictive performance measures used to compare accuracy of ANN models are:


RMSE - (root mean squared error) measures the distance between estimated and actual outcomes. Other metrics that measure the same concept are MSE, MAE or MPE.
R square - (R^2 or coefficient of determination) measures the reduction of variance when using the model.


When comparing two different ANN models for performance, metrics that take into account the complexity of the model may be used, such as AIC or BIC.