New
Book "Data
Mining in Finance: Advances in Relational and Hybrid Methods"
by Boris Kovalerchuk and Evgenii Vityaev, Kluwer Acad.
Publ, 2000 (ISBN: 0-7923-7804-0)
Kluwer's flyer
Buying info:
Amazon.com
Barnes&Noble
Kluwer Kluwer Academic
Publishers, P.O. Box 358, Accord Station, Hingham, MA, USA 02018-0358,
Tel: 781-871-6600, Fax: 781-681-9045
CONTENTS
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
Complete
contents
Comments
on the Microsoft draft standard (specification) for Data Mining (html)
pdf
April 23, 2000
WEB GUIDE DATA
MINING IN FINANCE
General Data Mining, Knowledge
Discovery and Machine Learning
Data Mining, Knowledge Discovery
and Machine Learning in Finance
Glossary
Computational
Finance Education
Neural
Networks in Finance
Other
Methods in Finance
Systems
on web
Journals
Conferences
People
Business
Intelligence Community
Financial
data
Financial
Data Mining Sites
Jobs
Bibliography
and Bookshop
Related
links
Hybrid
and Relational Data Mining in Finance
Glossary
Relational
Methods Based on First-Order Rules and Statistics
Methods
Based on Propositional Rules, Neural Networks, and Regression
Other
Sources and Hybrid Methods in Finance
Learning
Criteria
Relational
Machine Learning and Relational Data Bases
Other related links
Market
info
Business
Resources
Banking
and Finance
Financial
humor
Financial
humor (more)
Contact us
B. Kovalerchuk
(Central Washington University)
E.
Vityaev (Institute of Mathematics, Russian Academy of Sciences)