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Adaptive algorithm for training pRAM neural networks on unbalanced data sets

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3 Author(s)
Ramanan, S. ; Dept. of Electron. Syst. Eng., Essex Univ., Colchester, UK ; Clarkson, T.G. ; Taylor, J.G.

A novel algorithm for training pyramidal pRAM neural networks on an unbalanced training set is proposed. The behaviour of the standard reinforcement learning algorithm is analysed and an adaptive learning rate algorithm that modifies the reinforcement learning algorithm based on readily available a priori class probability is developed

Published in:

Electronics Letters  (Volume:34 ,  Issue: 13 )