Using Data Mining Techniques in Macroeconomic Analysis on Romania’s Case

In the present data mining techniques are the most utilized methods of calculus in discovering existent relations between different components, objects, phenomenon, etc. Economic analysis must be achieved by the most advanced methods of calculus, so that eventually, thanks to their evolution, they can generate much more viable data by minimizing information loss in order to better reflect reality. Romania, as an EU country, is in direct competition with other European countries, classifying in the category of countries heavily dependent on external commerce, and so, by economic relations with other countries. At the same time, its EU membership grants Romania the possibility to develop and implement strategies with regards to economic performance development, in order to better utilize external production factors. In this context, this paper will try to complete a macroeconomic analysis of relations between European GDP, Romanian GDP, EU population, Romania's population, Romania's imports from the EU and its exports to the EU using data mining techniques. Key-words: data mining, main component analysis, cluster analysis, discriminant analysis, GDP, interest rate, entropy, Bayesian classification, SAS, EU.