Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Evolved Decision Trees as Conformal Predictors
Högskolan i Borås, Institutionen Handels- och IT-högskolan.ORCID-id: 0000-0003-0412-6199
Högskolan i Borås, Institutionen Handels- och IT-högskolan.
Högskolan i Borås, Institutionen Handels- och IT-högskolan.ORCID-id: 0000-0003-0274-9026
Högskolan i Borås, Institutionen Handels- och IT-högskolan.
2013 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In conformal prediction, predictive models output sets of predictions with a bound on the error rate. In classification, this translates to that the probability of excluding the correct class is lower than a predefined significance level, in the long run. Since the error rate is guaranteed, the most important criterion for conformal predictors is efficiency. Efficient conformal predictors minimize the number of elements in the output prediction sets, thus producing more informative predictions. This paper presents one of the first comprehensive studies where evolutionary algorithms are used to build conformal predictors. More specifically, decision trees evolved using genetic programming are evaluated as conformal predictors. In the experiments, the evolved trees are compared to decision trees induced using standard machine learning techniques on 33 publicly available benchmark data sets, with regard to predictive performance and efficiency. The results show that the evolved trees are generally more accurate, and the corresponding conformal predictors more efficient, than their induced counterparts. One important result is that the probability estimates of decision trees when used as conformal predictors should be smoothed, here using the Laplace correction. Finally, using the more discriminating Brier score instead of accuracy as the optimization criterion produced the most efficient conformal predictions.

Ort, förlag, år, upplaga, sidor
IEEE , 2013.
Nyckelord [en]
Conformal prediction, Genetic programming, Data mining, Machine Learning
Nationell ämneskategori
Datavetenskap (datalogi) Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:hj:diva-38092DOI: 10.1109/CEC.2013.6557778ISI: 000326235301102Lokalt ID: 0;0;miljJAILISBN: 978-1-4799-0453-2 (tryckt)OAI: oai:DiVA.org:hj-38092DiVA, id: diva2:1163322
Konferens
IEEE Congress on Evolutionary Computation, 20-23 June 2013
Anmärkning

Sponsorship:

Swedish Foundation

for Strategic Research through the project High-Performance

Data Mining for Drug Effect Detection (IIS11-0053) and the

Knowledge Foundation through the project Big Data Analytics

by Online Ensemble Learning (20120192).

Tillgänglig från: 2017-12-06 Skapad: 2017-12-06 Senast uppdaterad: 2019-08-23Bibliografiskt granskad

Open Access i DiVA

fulltext(1131 kB)107 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 1131 kBChecksumma SHA-512
6f50a86fa663e15110ae48699c1680bfd761568249a1927e687299294a9b94e9da80c0f785c03f9ea9b3d828a88b64dfaee09857626d3928498bb99d05eb5d6c
Typ fulltextMimetyp application/pdf

Övriga länkar

Förlagets fulltext

Sök vidare i DiVA

Av författaren/redaktören
Johansson, UlfLöfström, Tuve
Datavetenskap (datalogi)Data- och informationsvetenskap

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 107 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 106 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf