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| ContributingAuthors Introduction： Knowledge Discovery Exploratory Data Analysis and Data Mining Traditional Methods Self-Organizing Maps Simple Example：Mapping Scotch Whiskies Overview Part 1：Applications 1 Let Financial Data Speakfor Themselves Carlos Serrano-Cinca 1.1 Initial Analysis of Financial Data 1.2 SOM as a Tool for Initial Data Analysis 1.3 Integrating SOM into a Decision。Support System 2 Projection ofLong-term Interest Rates with Maps Eric de Bodt,Philippe Gr3goire and Marie Cottrell 2.1 Introduction 2.2 Building Blocks 2.3 Simulating Future Behavior using Historical Information. 2.4 Application 2.5 Validation 2.6 Extension to Value-at-Risk 2 7 Conclusions 3 Picking Mutual Funds with Self-Organizing Maps Guido Deboeck 3.1 Exploratory Data Analysis 3.2 Morningstar Mutual Fund Database 3.3 A Simple Binary Example 3.4 Mapping Mutual Funds 3.5 Conclusions 4 Maps for Analyzing Failures of Small and Medium.sized Enterprises Kimmo Kiviluoto and Pentti Bergius 4.1 Corporate Failure-Causes and Symptoms 4.2 Self-Organizing Map as a Tool for Financial Statement Analys 4.3 The Data 4.4 Results 4.5 Summary 5 SeIf-Organi2ingAtlas ofRussian Banks Serge Shumsky andA.V Yarovoy 5.1 Introduction， 5.2 Overview ofthe Russian Banking System. 5.3 Problem Formulation 5.4 Linear Analysis using PCA 5.5 Nonlinear Analysis or the Nonlinear PCA Extension 5.6 SOM of Russian Banks 5.7 A SOM Atlas of Russian Banks in 1994 5.8 Evolution of Russian Banking from 1994 to 1995 5.9 Conclusions 6 Investment Maps ofEmerging Markets Guido Deboeck 6.1 Background 6.2 Performance and Risks of Investing in Emerging Markets 6.3 Patterns Among Emerging Markets 6.4 Strategic Implications of SOM for Investments in Emerging Markets 6.5 Conclusions Color Plate Section follows Chapter 6 7 A Hybrid Neural Network System for Trading Financial Markets Marina Resta 7.1 Introduction 7.2 ISOG：Integrated Selforganization and Genetics …… 8 Real Estate Investment Appraisal of Land Properties using SOM by Eero Carlson 9 Real Estate Investment Appraisal of Buildings using SOM by Anna Tulkki 10 Differential Patterns in Consumer Purchase Preferences using Self-Organizing Maps: A Case Study of China by Bernd Schmitt and Guido Deboeck Ptrt 2 Methodology, Tools and Techniques 11 The SOM Methodology by Teuvo Kohonen 12 Self-Organizing Maps of Large Document Collections by Timo Honkela and Krista Lagus and Samuel Kaski 13 Software Tools for Self-Organizing Maps by Guido Deboeck 14 Tips for Processing and Color-coding of Self-Organizing Maps by Samuel Kaski and Teuvo Kohanen 15 Best Practices in Data Mining using Self-Organizing Maps by Guido Deboeck Notes Glossary Bibliography |
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