Abstract
Micro economic modelling which includes macro economic factors is often avoided in many commercial data mining projects due to the presence of factors which are difficult to predict and the complexity of bringing together data from diverse sources. In this paper we present a methodology and a set of contrasting algorithms to mine complex data with many unknown factors and for factors whose uncertainty is interrelated. Multiple segmentation, classification techniques and predictive algorithms all play a part in incorporating and controlling uncertainty while guaranteeing precise and reliable information as the end product. To illustrate the approach, we describe a data mining project carried out with the Port of Barcelona, which considers specific business data together with national and international macro-economic indicators.
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