Financial Data Analysis with PGMs Using AMIDST

Rafael Cabanas, Ana M. Martinez, Andres R. Masegosa, Dario Ramos-Lopez, Antonio Sameron, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

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Abstrakt

The AMIDST Toolbox an open source Java 8 library for scalable learning of probabilistic graphical models (PGMs) based on both batch and streaming data. An important application domain with streaming data characteristics is the banking sector, where we may want to monitor individual customers (based on their financial situation and behavior) as well as the general economic climate. Using a real financial data set from a Spanish bank, we have previously proposed and demonstrated a novel PGM framework for performing this type of data analysis with particular focus on concept drift. The framework is implemented in the AMIDST Toolbox, which was also used to conduct the reported analyses. In this paper, we provide an overview of the toolbox and illustrate with code examples how the toolbox can be used for setting up and performing analyses of this particular type.

OriginalsprogEngelsk
TitelProceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
Antal sider4
ForlagIEEE
Publikationsdato30 jan. 2017
Sider1284-1287
Artikelnummer7836816
ISBN (Elektronisk)978-1-5090-5910-2
DOI
StatusUdgivet - 30 jan. 2017
Begivenhed16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 - Barcelona, Spanien
Varighed: 12 dec. 201615 dec. 2016

Konference

Konference16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
LandSpanien
ByBarcelona
Periode12/12/201615/12/2016
SponsorIEEE Computer Society

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Citationsformater

Cabanas, R., Martinez, A. M., Masegosa, A. R., Ramos-Lopez, D., Sameron, A., Nielsen, T. D., Langseth, H., & Madsen, A. L. (2017). Financial Data Analysis with PGMs Using AMIDST. I Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 (s. 1284-1287). [7836816] IEEE. https://doi.org/10.1109/ICDMW.2016.0185