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
|
2. Numerical Data Mining Models with Financial Applications
Contents
- Statistical, autoregression models
- Financial applications of autoregression models
- Instance-based learning and financial applications
- Neural networks
- Neural networks and hybrid systems in finance
- Recurrent neural networks in finance
- Modular networks and genetic algorithms
- Testing results and the complete round robin method
- Expert mining
- Interactive learning of monotone Boolean
- functions
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