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
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