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Titlebook: Domain Driven Data Mining; Longbing Cao,Philip S. Yu,Yanchang Zhao Book 2010 Springer-Verlag US 2010 data analysis.data mining.decision su

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Mining Actionable Knowledge on Capital Market Data, an experienced trader may use an appropriate pairs trading strategy, namely taking a long position in the stock of one company and shorting the stock of another in the same sector. A long position reflects the view that the stock price will rise; shorting reflects the opposite. This strategy may st
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Book 2010tactics, and performance. In turn, data mining has emerged as one of the most active areas in information technologies. .Domain Driven Data Mining. offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actiona
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Brief Book Description and Book Assumptionsmation about the experience and performance of government service objectives and social security policies, and may include evidence and indicators for recovering, detecting, preventing and predicting debt occurrences.
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Brian J. Linder M.D.,Daniel S. Elliott M.D.summarize them, and use visualisation techniques to make them easy to read and understand [242]. The function of post-mining in knowledge discovery process is shown in Figure 8.1, which bridges the gap between the patterns discovered by data mining techniques and the useful knowledge desired by end users.
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Mining Actionable Knowledge on Social Security Data,mation about the experience and performance of government service objectives and social security policies, and may include evidence and indicators for recovering, detecting, preventing and predicting debt occurrences.
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Unifying Causality and Psychologyatistically increase profit while decreasing risk compared to a naive strategy of putting all money on one stock. In practice, an actionable strategy can not only maximize the profit or return, but also result in the proper management of risk and trading costs.
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