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
Getting
the book:
Amazon.com
Barnes&Noble
Springer/Kluwer
|
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
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