Data Mining in Finance

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Book

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

CONTENTS
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

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4. Relational Data Mining (RDM)

Contents

  • Introduction
  • Examples
  • Relational data mining paradigm
  • Challenges and obstacles in relational data mining
  • Theory of RDM
  • Background knowledge
  • Algorithms: FOIL and FOCL
  • Algorithm MMDR
  • Numerical relational data mining
  • Data types
  • Empirical axiomatic theories: empirical contents of data