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Data Mining Models and Enterprise Risk Management

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Enterprise Risk Management Models

Part of the book series: Springer Texts in Business and Economics ((STBE))

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Abstract

The advent of big data has led to an environment where billions of records are possible. Data mining is demonstrated on a financial risk set of data using R (Rattle) computations for the basic classification algorithms in data mining. We have not demonstrated that scope by any means, but have demonstrated small-scale application of the basic algorithms. The intent is to make data mining less of a black-box exercise, thus hopefully enabling users to be more intelligent in their application of data mining.

We demonstrate an open source software product. R is a very useful software, widely used in industry and has all of the benefits of open source software (many eyes are monitoring it, leading to fewer bugs; it is free; it is scalable). Further, the R system enables widespread data manipulation and management.

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Olson, D.L., Wu, D. (2020). Data Mining Models and Enterprise Risk Management. In: Enterprise Risk Management Models. Springer Texts in Business and Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-60608-7_9

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  • DOI: https://doi.org/10.1007/978-3-662-60608-7_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-60607-0

  • Online ISBN: 978-3-662-60608-7

  • eBook Packages: Economics and FinanceEconomics and Finance (R0)

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