Choices and pitfalls concerning mixture-of-experts modeling

Denise B Ferrari; Armando Z Milioni

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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Choices and pitfalls concerning mixture-of-experts modeling

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Author(s):	Denise B Ferrari ^[1] ; Armando Z Milioni ^[2] Total Authors: 2
Affiliation:	^[1] Instituto Tecnológico de Aeronáutica ^[2] Instituto Tecnológico de Aeronáutica Total Affiliations: 2
Document type:	Journal article
Source:	Pesquisa Operacional; v. 31, n. 1, p. 95-111, 2011-04-00.
Abstract
This paper deals with some important decisions that ought to be made when building a mixture-of-experts model (MEM). Such decisions are related to aspects such as the clustering method and the gating functions used in the model. Depending on how these decisions are made, different mixtures might be formed, yielding different results. In the present study, we investigate the way such decisions affect the performance of MEM's, when using statistical models to regression problem. The famous Boston housing data is used as illustration for the technique (AU)

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