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bmaw2014_paper_8.pdf
Preview of http://ceur-ws.org/V ol-1218/bmaw2014_pap er_8.pdf
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📊 Size: 2.16 MB
📄 Pages: 10 pages
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Summary

The authors compare Gaussian, Laplace, and horseshoe shrinkage priors, finding the horseshoe prior has the best predictive performance. They also implement projective covariate selection to identify a subset of predictive biomarkers, allowing for cost-efficient prediction without significant loss in performance. The study uses data from 7932 Finnish individuals, including 401 with diabetes, and a 15-year follow-up period. The results show that incorporating non-diabetic individuals into the analysis improves predictive performance, and the horseshoe prior effectively shrinks irrelevant biomarkers while retaining relevant ones.

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The authors compare Gaussian, Laplace, and horseshoe shrinkage priors, finding the horseshoe prior has the best predictive performance.

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  • File Format: PDF
  • File Size: 2.16 MB
  • Pages: 10
  • Language: EN
  • Total Downloads: 47
  • Last Updated: 21 hours ago

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