Macroscopic properties of the cost function of a feed - forward neural network prior to training
نویسنده
چکیده
By making simple assumptions regaxding the nodal potentials we have been able to obtain analytic expmions for the meam and standard deviation of the cost-function values of a feed-faward multilayer network, with continuous activation units, prior to mining. We have also obtained means of the derivatives. with respect to the weights and biases, of the cost function. The expressions have been used to obtain systematic estimates of the learning rate required for back-propagation mining. The results are exemplified using an 8 3 4 encoder "eoYOTk.
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