An affinity matrix approach for structure selection of extreme learning machines.
David Pinto, André Lemos, Antônio P. Braga · The European Symposium on Artificial Neural Networks · 2015
This paper proposes a novel pruning approach for Extreme Learning Machines. Hidden neurons ranking and selection are performed using a priori information expressed by anity matrices. We show that the similarity between the anity matrix of the input patterns and the anity matrix of the hidden layer output patterns can be seen as a mea- sure of the data structural retention through the network. However, from a certain similarity level, adding new hidden nodes will have small or no eect on the amount of information propagated from the input. The pro- posed approach automatically determines this level and hence the suitable number of hidden nodes. Experiments are performed using classication problems to validate the proposed approach.