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Instance Ranking using Ensemble Spread
University of Borås, Sweden.
University of Borås, Sweden.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. (Skövde Cognition and Artificial Intelligence Lab (SCAI))
2007 (English)In: Proceedings of the 2007 International Conference on Data Mining: DMIN 2007 / [ed] Robert Stahlbock, Sven F. Crone, Stefan Lessmann, Hamid R. Arabnia, CSREA Press, 2007, p. 73-78Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates a technique for predicting ensemble uncertainty originally proposed in the weather forecasting domain. The overall purpose is to find out if the technique can be modified to operate on a wider range of regression problems. The main difference, when moving outside the weather forecasting domain, is the lack of extensive statistical knowledge readily available for weather forecasting. In this study, three different modifications are suggested to the original technique. In the experiments, the modifications are compared to each other and to two straightforward technniques, using ten publicly available regression problems. Three of the techniques show promising result, especially one modification based on genetic algorithms. The suggested modification can accurately determine whether the confidence in ensemble predictions should be high or low.

Place, publisher, year, edition, pages
CSREA Press, 2007. p. 73-78
National Category
Meteorology and Atmospheric Sciences Computer Sciences
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3695ISBN: 1-60132-031-0 (print)ISBN: 978-1-60132-031-5 (print)OAI: oai:DiVA.org:his-3695DiVA, id: diva2:293624
Conference
International Conference on Data Mining, DMIN 2007, June 25-28, 2007, Las Vegas, Nevada, USA
Available from: 2010-02-12 Created: 2010-02-12 Last updated: 2025-02-01Bibliographically approved

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http://www.dmin-2007.com/

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Niklasson, Lars

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CiteExportLink to record
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Citation style
  • apa
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  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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