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Synergy conformal p...
Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning
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- Norinder, Ulf, 1956- (författare)
- Uppsala universitet,Stockholms universitet,Örebro universitet,Institutionen för naturvetenskap och teknik,Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden; Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden,MTM Research Centre,Institutionen för data- och systemvetenskap,Uppsala University, Sweden; Örebro University, Sweden,Institutionen för farmaceutisk biovetenskap,Stockholm Univ, Dept Comp & Syst Sci; Örebro Univ, MTM Res Ctr, Sch Sci & Technol
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- Spjuth, Ola, Professor, 1977- (författare)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Science for Life Laboratory, SciLifeLab
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- Svensson, Fredrik (författare)
- Alzheimer's Research UK UCL Drug Discovery Institute, University College London, The Cruciform Building, Gower Street, London, UK,UCL, Alzheimers Res UK UCL Drug Discovery Inst, England
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(creator_code:org_t)
- 2021-10-02
- 2021
- Engelska.
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Ingår i: Journal of Cheminformatics. - : Chemistry Central. - 1758-2946. ; 13:1
- Relaterad länk:
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https://doi.org/10.1...
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https://jcheminf.bio...
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https://uu.diva-port... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Confidence predictors can deliver predictions with the associated confidence required for decision making and can play an important role in drug discovery and toxicity predictions. In this work we investigate a recently introduced version of conformal prediction, synergy conformal prediction, focusing on the predictive performance when applied to bioactivity data. We compare the performance to other variants of conformal predictors for multiple partitioned datasets and demonstrate the utility of synergy conformal predictors for federated learning where data cannot be pooled in one location. Our results show that synergy conformal predictors based on training data randomly sampled with replacement can compete with other conformal setups, while using completely separate training sets often results in worse performance. However, in a federated setup where no method has access to all the data, synergy conformal prediction is shown to give promising results. Based on our study, we conclude that synergy conformal predictors are a valuable addition to the conformal prediction toolbox.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- Confidence
- Conformal prediction
- Federated learning
- Machine learning
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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