What does the relative sum of squares error signify in neural network analysis in SPSS? What range of values of the relative sum of sqaures error is acceptable for a good neural network? I am getting around 0.9 of the relative error for 1 model and around 0.4 for another. Are both the networks significant?
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  A value closer to 0 indicates that the model has a smaller random error component, and that the fit will be more useful for prediction.