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Venn predictors for well-calibrated probability estimation trees
University of Borås, Faculty of Librarianship, Information, Education and IT.
University of Borås, Faculty of Librarianship, Information, Education and IT.ORCID iD: 0000-0003-0274-9026
University of Borås, Faculty of Librarianship, Information, Education and IT.
University of Borås, Faculty of Librarianship, Information, Education and IT.
Show others and affiliations
2018 (English)In: 7th Symposium on Conformal and Probabilistic Prediction and Applications: COPA 2018, 11-13 June 2018, Maastricht, The Netherlands / [ed] Alex J. Gammerman and Vladimir Vovk and Zhiyuan Luo and Evgueni N. Smirnov and Ralf L. M. Peeter, 2018, p. 3-14Conference paper, Published paper (Refereed)
Abstract [en]

Successful use of probabilistic classification requires well-calibrated probability estimates, i.e., the predicted class probabilities must correspond to the true probabilities. The standard solution is to employ an additional step, transforming the outputs from a classifier into probability estimates. In this paper, Venn predictors are compared to Platt scaling and isotonic regression, for the purpose of producing well-calibrated probabilistic predictions from decision trees. The empirical investigation, using 22 publicly available datasets, showed that the probability estimates from the Venn predictor were extremely well-calibrated. In fact, in a direct comparison using the accepted reliability metric, the Venn predictor estimates were the most exact on every data set.

Place, publisher, year, edition, pages
2018. p. 3-14
Series
Proceedings of Machine Learning Research
Keywords [en]
Venn predictors, Calibration, Decision trees, Reliability
National Category
Computer Sciences
Research subject
Business and IT
Identifiers
URN: urn:nbn:se:hb:diva-15061OAI: oai:DiVA.org:hb-15061DiVA, id: diva2:1245201
Conference
7th Symposium on Conformal and Probabilistic Prediction and Applications, London, June 11th - 13th, 2018
Funder
Knowledge FoundationAvailable from: 2018-09-04 Created: 2018-09-04 Last updated: 2018-09-06Bibliographically approved

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Other links

http://proceedings.mlr.press/v91/johansson18a/johansson18a.pdf

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Johansson, UlfLöfström, TuveSundell, HåkanLinnusson, HenrikGidenstam, AndersBoström, Henrik

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Johansson, UlfLöfström, TuveSundell, HåkanLinnusson, HenrikGidenstam, AndersBoström, Henrik
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CiteExportLink to record
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Citation style
  • apa
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Output format
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