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A Novel Technique to Design an Adaptive Committee of Models Applied to Predicting Company’s Future Performance
Kaunas University of Technology, Kaunas, Lithuania.
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). Kaunas University of Technology, Kaunas, Lithuania.ORCID-id: 0000-0003-2185-8973
Kaunas University of Technology, Kaunas, Lithuania.
Kaunas University of Technology, Kaunas, Lithuania.
2013 (engelsk)Inngår i: International Conference on Computer Research and Development: ICCRD 2013 / [ed] Fan Yama, New York, NY: ASME Press, 2013, s. 65-70Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This article presents an approach to designing an adaptive, data dependent, committee of models applied to prediction of several financial attributes for assessing company’s future performance. A self-organizing map (SOM) used for data mapping and analysis enables building committees, which are specific (committee size and aggregation weights) for each SOM node. The number of basic models aggregated into a committee and the aggregation weights depend on accuracy of basic models and their ability to generalize in the vicinity of the SOM node. The proposed technique led to a statistically significant increase in prediction accuracy if compared to other types of committees.

sted, utgiver, år, opplag, sider
New York, NY: ASME Press, 2013. s. 65-70
Emneord [en]
Committee, Random forest, SOM, Data proximity, Financial attribute
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-24666DOI: 10.1115/1.860182_ch11ISBN: 978-0-7918-6018-2 OAI: oai:DiVA.org:hh-24666DiVA, id: diva2:698529
Konferanse
5th International Conference on Computer Research and Development (ICCRD 2013), Ho Chi Minh City, Vietnam, February 23-24, 2013
Tilgjengelig fra: 2014-02-23 Laget: 2014-02-23 Sist oppdatert: 2014-11-17bibliografisk kontrollert

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Totalt: 136 treff
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