Resumen

SANTOS, Omar J. S.  y  MILIONI, Armando Z.. Mixture of Local Experts Model for Data Classification. Inv. Op. [online]. 2005, vol.25, n.1, pp.105-121. ISSN 0874-5161.

In this paper we present a Mixture of Local Experts Model (MLEM) for data classification. The discriminant tools applied are Fisher's Discriminant Analysis, Logistic Regression and a non-parametric model called Extended DEA-DA (Sueyoshi, 2004). Using real data, we compare the results obtained with the MLEM, which requires data clusterization and solution investigation on each cluster, against results obtained with a more orthodox approach, which is classification over the entire data set. The main conclusion is that even though it seems to be a promising technique, the additional effort in building a MLEM does not assure better results.

Palabras clave : Mixture of Local Expert Models; Discriminant Analysis; Clustering; Extended DEA-DA.

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