Composi？？o de especialistas locais para classifica？？o de dados

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.