Data mining in finance: advances in relational and hybrid methods

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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 focuses specifically on relational data mining (RDM), which is a learning method able to learn more expressive rules than other symbolic approaches. RDM is thus better suited for financial mining, because it is able to make ...

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Data Mining in Finance: Advances in Relational and Hybrid Methods
2013, Springer

ISBN-13: 9781475773323

2000 edition

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Data Mining in Finance: Advances in Relational and Hybrid Methods
2000, Springer, Boston, MA

ISBN-13: 9780792378044

2000 edition

Hardcover

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