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Data mining in finance : advances in relational and hybrid methods /
"Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, rule-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The bo...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boston : Norwell, Mass :
Kluwer Academic Publishers ; Distributors for North, Central, and South America, Kluwer Academic Publishers,
©2000.
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| Colección: | Kluwer international series in engineering and computer science ;
SECS 547. |
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| Acceso en línea: | Texto completo |
| Sumario: | "Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, rule-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The book focuses specifically on relational data mining (RDM), which is a learning method able to learn more expressive rules than other symbolic approaches." "Data Mining in Finance introduces a new approach, combining relational data mining with the analysis of statistical significance of discovered rules. This reduces the search space and speeds up the algorithms. The book also presents interactive and fuzzy logic tools for "mining" the knowledge from the experts, further reducing the search space." "Data Mining in Finance contains a number of practical examples of forecasting S & P 500, exchange rates, stock directions, and rating stocks for portfolio, allowing interested readers to start building their own models. This book is an excellent reference for researchers and professionals in the fields of artificial intelligence, machine learning, data mining, knowledge discovery, and applied mathematics."--Jacket |
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| Descripción Física: | 1 online resource (xiv, 308 pages) : illustrations |
| Bibliografía: | Includes bibliographical references and index. Includes bibliographical references (pages 285-298) and index. |
| ISBN: | 0306470187 9780306470189 9780792378044 0792378040 6610206031 9786610206032 |