I have a set of matrix where the last column is the

**RESPONSE VECTOR**.

I have performed a backprop NN (neural network) in order to perform a nonlinear regression on this set of matrix.

Thus, in the end, the NN will spit out the

**PREDICTED RESPONSE VECTOR**.

I was performing a

**One-Way Anova**to obtaiin the F-ratio and p-value via the ANOVA1 matlab toolbox. The input was a matrix consisting of both the RESPONSE VECTOR and the PREDICTED RESPONSE VECTOR. The concanation was done column wise.

In this case, would the F-ratio and p-value be valid in determining whether the yielded NN model is good or not?

Is using ANOVA1 in anyway valid in this case?

Thank you very much.