Data Mining in Finance Advances in Relational and Hybrid Methods /

• Κύριοι συγγραφείς: Kovalerchuk, Boris (Συγγραφέας), Vityaev, Evgenii (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US, 2002.
• Σειρά: The International Series in Engineering and Computer Science, 547
• Θέματα: Computer science.; Finance.; Data structures (Computer science).; Artificial intelligence.; Computer Science.; Data Structures, Cryptology and Information Theory.; Artificial Intelligence (incl. Robotics).; Finance, general.

Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The book fo...

Πίνακας περιεχομένων:

• The scope and methods of the study
• Numerical Data Mining Models and Financial Applications
• Rule-Based and Hybrid Financial Data Mining
• Relational Data Mining (RDM)
• Financial Applications of Relational Data Mining
• Comparison of Performance of RDM and other methods in financial applications
• Fuzzy logic approach and its financial applications.