The correlation as cost function in neural networks
Harald Englisch, Ypke Hiemstra · 2002
It is shown that in time series forecasting by feedforward neural nets with a nonlinear transfer function for the output unit the minimization of the usual cost function, the mean squared error, is not equivalent to the maximization of the correlation. A simple modification of the neural net is proposed which restores the equivalence known from linear regression.>