Data Mining in Finance


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Data Mining in Finance: Advances in Relational and Hybrid Methods
by Boris Kovalerchuk and Evgenii Vityaev,
Kluwer Acad. Publ, 2000

The Kluwer International Series in Engineering and Computer Science , Vol.  547  

ISBN: 0-7923-7804-0
Kluwer's prepublication flyer, 2000 (pdf)

Foreword by Gregory Piatetsky-Shapiro

1. The Scope and Methods of the Study
2. Numerical Data Mining Models with  Financial    Applications
3. Rule-Based and Hybrid Financial Data Mining
4. Relational Data Mining (RDM)
5. Financial Applications of Relational Data Mining
6. Comparison of Performance of RDM and other methods in financial applications
7. Fuzzy logic approach and its financial applications

Getting the book:   

7. Fuzzy logic approach and its financial applications


  • Knowledge discovery and fuzzy logic
  • "Human logic" and mathematical principles of uncertainty
  • Difference between fuzzy logic and probability theory
  • Basic concepts of fuzzy logic
  • Inference problems and solutions
  • Constructing coordinated contextual linguistic variables
  • Constructing coordinated fuzzy inference
  • Fuzzy logic in finance