Article ID: | iaor20031304 |
Country: | Netherlands |
Volume: | 43 |
Issue: | 4 |
Start Page Number: | 787 |
End Page Number: | 800 |
Publication Date: | Sep 2002 |
Journal: | Computers & Industrial Engineering |
Authors: | Zanakis Stelios H., Becerra-Fernandez Irma, Walczak Steven |
Keywords: | risk, datamining |
This paper presents the insights gained from applying knowledge discovery in databases (KDD) processes for the purpose of developing intelligent models, used to classify a country's investing risk based on a variety of factors. Inferential data mining techniques, like C5.0, as well as intelligent learning techniques, like neural networks, were applied to a dataset of 52 countries. The dataset included 27 variables (economic, stock market performance/risk and regulatory efficiencies) on 52 countries, whose investing risk category was assessed in a