Data Mining and Model Trees Study on GDP and its Influence Factors

摘要

In this paper we turn to several methods of data mining, such as model trees and linear regression to explore the implications in the evolution and patterns of Romanian GDP. Data used in the research is made of statistics, socio-economic indicators tables and reports from the Romanian National Institute of Statistics over the 2000-2011 period. We wanted to investigate GDP patterns apart from typical ways, through salaries level, employers' social contributions from diverse fields of economy (agriculture, industry, commerce, construction, services, financial, banking, etc.) as well as taxes on production and imports, all integrated in the data mining tasks.