Confidence for exploratory machine learning

Peter Salamon, David Salamon, V. Adrian Cantu, Michelle An, Tyler Perry, Robert A. Edwards, Anca M. Segall

Research output: Contribution to journalMeeting Abstractpeer-review

Abstract

Machine learning problems performing classification into categories whose definition and validity come from a necessary dialogue with the machine learning system represent a special class of problems we call “exploratory”. Here we argue that such problems need special treatment and illustrate this to be the case for confidence calibration in gene function prediction.
Original languageEnglish
Article number1365-Pos
Pages (from-to)281a
Number of pages1
JournalBiophysical Journal
Volume122
Issue number3 Suppl. 1
DOIs
Publication statusPublished - 10 Feb 2023
Externally publishedYes
Event67th Biophysical Society Annual Meeting: Biophysics beyond the boundaries - San Diego, United States
Duration: 18 Feb 202322 Feb 2023
Conference number: 67th

Bibliographical note

Abstract for poster presented at the meeting Monday, February 20, 2023.

Keywords

  • Machine learning
  • Gene function prediction.
  • Confidence calibration

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