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Best Practices in Data Mining using Self-Organizing Maps

  • Guido Deboeck
Part of the Springer Finance book series (FINANCE)

Abstract

This chapter summarizes best practices in data mining and visual data explorations through clustering of multi-dimensional data in finance, economics and marketing. The best practices outlined in this chapter are based on (i) the lessons learned from all the chapters in this book, (ii) lessons learned from other papers not included here, (iii) the expertise of people who have several years of hands-on experience in applying neural networks in finance and economics. From the applications presented in this book we derived a process for data analysis, clustering, visualization, and evaluation in finance, economics and marketing. This chapter outlines this process and illustrates it by applying it to country credit risks analysis.

Keywords

Input Vector Mutual Fund Credit Risk Wall Street Journal European Monetary Union 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Guido Deboeck

There are no affiliations available

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