Switching Neural Network: An application to Regression Problems

Authors:
Enrico Ferrari;Marco Muselli
Affiliations:
Institute of Electronics, Computer and Telecommunication Engineering, Italian National Research Council, Italy;Institute of Electronics, Computer and Telecommunication Engineering, Italian National Research Council, Italy
Venue:
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
Year:
2011

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Abstract

In this paper regression problems, in which the output is continuous or discrete, are considered. In particular, the Switching Neural Network approach, which has been introduced for classification, is properly extended to deal with regression tasks. The resulting model, named SNN-reg, presents multiple advantages, involving both the quality of the obtained solution and the computational effort needed for its generation. Moreover, SNN-reg allows a regression function to be swritten in terms of a set of intelligible rules, which can be interpreted by the user.