Abstract
This paper considers one of the contemporary advanced analytics applications named Puzzle methods. It is studied aiming at novel results in collaborative statistical and logical research based on quantitative method applications, deep processing of accumulated knowledge, etc. It is shown that applications of intelligent technologies advance the efficiency of statistical applications. Financial and security systems (SS) have been considered as an example of difficult-to-explore areas. Original results are presented on how to build more effective logical-and-statistical applications by using novel puzzle methodologies. It is shown that all the demonstrated advantages may be successfully combined with other known methods from advanced analytics, knowledge discovery, data/web/deep data mining or other fields. Also it is shown how the considered applications enhance the quality of statistical inference, improve the human-machine interaction between the user and system and hence serve the process of sustainable improvement of the results. Applications to SAS Enterprise Miner reveal the strength of the proposed Puzzle methods.
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Jotsov, V.S., Iliev, E. (2015). Applications of Advanced Analytics Methods in Sas Enterprise Miner. In: Filev, D., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-319-11310-4_36
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DOI: https://doi.org/10.1007/978-3-319-11310-4_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11309-8
Online ISBN: 978-3-319-11310-4
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