Choices and pitfalls concerning mixture-of-experts modeling

Denise Ferrari, Armando Zeferino Milioni

Pesquisa Operacional · 2011 · 10 citations · 13 references

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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

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