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Aggregating predictions using Non-Disclosed Conformal Prediction
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

When data are stored in different locations and pooling of such data is not allowed, there is an informational loss when doing predictive modeling. In this thesis, a new method called Non-Disclosed Conformal Prediction (NDCP) is adapted into a regression setting, such that predictions and prediction intervals can be aggregated from different data sources without interchanging any data. The method is built upon the Conformal Prediction framework, which produces predictions with confidence measures on top of any machine learning method. The method is evaluated on regression benchmark data sets using Support Vector Regression, with different sizes and settings for the data sources, to simulate real life scenarios. The results show that the method produces conservatively valid prediction intervals even though in some settings, the individual data sources do not manage to create valid intervals. NDCP also creates more stable intervals than the individual data sources. Thanks to its straightforward implementation, data owners which cannot share data but would like to contribute to predictive modeling, would benefit from using this method.

Place, publisher, year, edition, pages
2019. , p. 38
Keywords [en]
Conformal Prediction, Non-Disclosed Conformal Prediction, Support Vector Regression, Reliable Machine Learning
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-385098OAI: oai:DiVA.org:uu-385098DiVA, id: diva2:1323531
Subject / course
Statistics
Educational program
Master Programme in Statistics
Supervisors
Examiners
Available from: 2019-06-18 Created: 2019-06-12 Last updated: 2019-06-18Bibliographically approved

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Department of Statistics
Probability Theory and Statistics

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CiteExportLink to record
Permanent link

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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
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