THE PROBABILISTIC NEURAL NET NEURON’S NUMBER CALCULATIONS - Shcherbacova, Galina; Krylov, Victor; Logvinov, Oleg (International Journal of Computing, 2014)
The sub-gradient method of estimation of the number of the hidden layer neurons of a probabilistic neural network is suggested. This method allows evaluating the data compactness violation in λ-space. This evaluation based on the noise stability sub-gradient iterative optimization method. This method allows reducing the number of the hidden layer neurons and classification time.