Abstract
This paper shows how a European mail order company uses data fusion in order to improve sales. To select the best data fusion algorithm, two traditional data fusion methods, that is, polytomeous logistic regression and nearest neighbour algorithms, are compared with two model-based clustering approaches. Finally, it is shown how internal and external validation criteria are used in order to evaluate the results of the data fusion algorithms.
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