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APPrOVE: Application-oriented Validation and Evaluation of Supervised Learners
Responsible organisation
2010 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

Learning algorithm evaluation is usually focused on classification performance. However, the characteristics and requirements of real-world applications vary greatly. Thus, for a particular application, some evaluation criteria are more important than others. In fact, multiple criteria need to be considered to capture application-specific trade-offs. Many multi-criteria methods can be used for the actual evaluation but the problems of selecting appropriate criteria and metrics as well as capturing the trade-offs still persist. This paper presents a framework for application-oriented validation and evaluation (APPrOVE). The framework includes four sequential steps that together address the aforementioned problems and its use in practice is demonstrated through a case study.

Place, publisher, year, edition, pages
London: IEEE press , 2010.
Keyword [en]
classification, evaluation, supervised learning
National Category
Software Engineering Computer Science
Identifiers
URN: urn:nbn:se:bth-7758Local ID: oai:bth.se:forskinfoBF98093116D46606C12577640038B637ISBN: 978-1-4244-5164-7 (print)OAI: oai:DiVA.org:bth-7758DiVA: diva2:835419
Conference
IEEE Intelligent Systems
Available from: 2012-09-18 Created: 2010-07-18 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(583 kB)101 downloads
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fb14cacd628b1235375389937e1eaa112def04aa537b0eac0c88dd9bbd19ef16de5f40296fc62fa625b188b046cac5a65147ed8d14f9a844d4cf64cd139984ab
Type fulltextMimetype application/pdf

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Lavesson, Niklas
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf