[PDF.70aq] Data Mining in Finance: Advances in Relational and Hybrid Methods (The Springer International Series in Engineering and Computer Science)

Data Mining in Finance: Advances in Relational and Hybrid Methods (The Springer International Series in Engineering and Computer Science)

[PDF.kh26] Data Mining in Finance: Advances in Relational and Hybrid Methods (The Springer International Series in Engineering and Computer Science)

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 | #5806760 in Books |  Boris Kovalerchuk |  2000-04-30 | Original language:English | PDF # 1 |  9.21 x.81 x6.14l,1.31 | File type: PDF | 308 pages

 | Data Mining In Finance Advances In Relational And Hybrid Methods

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||0 of 0 people found the following review helpful.| Good examples but missing explanations|By Sandro Saitta|With a title such as "Data Mining in Finance: Advances in Relational and Hybrid Methods", one can think that this book is a set of research papers in this topic. However, it is not the case. The authors, Kovalerchuk and Vityaev, have written more than 300 pages about applying data mining techniques in finance.

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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 ...

You easily download any file type for your gadget.Data Mining in Finance: Advances in Relational and Hybrid Methods (The Springer International Series in Engineering and Computer Science)   |  Boris Kovalerchuk, Evgenii Vityaev. Which are the reasons I like to read books. Great story by a great author.

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