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
|
3. Rule-Based and Hybrid Financial Data Mining
Contents
- Decision tree and DNF learning
- Decision tree and DNF learning in finance
- Extracting decision trees from neural networks
- Extracting decision trees from neural networks in finance
- Probabilistic rules and knowledge-based
- stochastic modeling
- Knowledge-based stochastic modeling in finance
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