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.

A constructive technique based on linear programming for training switching neural networks

M Muselli
2008

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.
2008
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
Switching Neural Network
constructive technique
positive Boolean function
Switch Programming.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/50078
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