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Neural Computing and Applications

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01.09.2012 | Original Article

SOMwise regression: a new clusterwise regression method

verfasst von: Jorge Muruzábal, Diego Vidaurre, Julián Sánchez

Erschienen in: Neural Computing and Applications | Ausgabe 6/2012

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Abstract

We present a novel neural learning architecture for regression data analysis. It combines, at the high level, a self-organizing map (SOM) structure, and, at the low level, a multilayer perceptron at each unit of the SOM structure. The goal is to build a clusterwise regression model, that is, a model recognizing several clusters in the data, where the dependence between predictors and response is variable (typically within some parametric range) from cluster to cluster. The proposed algorithm, called SOMwise Regression, follows closely in the spirit of the standard SOM learning algorithm and has performed satisfactorily on various test problems.

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Titel: SOMwise regression: a new clusterwise regression method
verfasst von: Jorge Muruzábal
Diego Vidaurre
Julián Sánchez
Publikationsdatum: 01.09.2012
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 6/2012
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-011-0536-3

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