A Constructive Technique Based on Linear Programming for Training Switching Neural Networks

Authors:
Enrico Ferrari;Marco Muselli
Affiliations:
Institute of Electronics, Computer and Telecommunication Engineering, Italian National Research Council, , Genoa, Italy 16149;Institute of Electronics, Computer and Telecommunication Engineering, Italian National Research Council, , Genoa, Italy 16149
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Year:
2008

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Abstract

A general constructive approach for training neural networks in classification problems is presented. This approach is used to construct a particular connectionist model, named Switching Neural Network (SNN), based on the conversion of the original problem in a Boolean lattice domain. The training of an SNN can be performed through a constructive algorithm, called Switch Programming(SP), based on the solution of a proper linear programming problem. Simulation results obtained on the StatLog benchmark show the good quality of the SNNs trained with SP.