The importance of hyperparameters selection within small datasets

Parivash Ashrafi, Yi Sun, Neil Davey, Rod Adams, Marc B. Brown, Maria Prapopoulou, Gary Moss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Gaussian Process is a Machine Learning technique that has been applied to the analysis of percutaneous absorption of chemicals through human skin. The normal, automatic method of setting the hyperparameters associated with Gaussian Processes may not be suitable for small datasets. In this paper we investigate whether a handcrafted search method of determining these hyperparameters is better for such datasets.

Original languageEnglish
Title of host publication2015 International Joint Conference on Neural Networks, IJCNN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2015-September
ISBN (Electronic)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
Publication statusPublished - 28 Sep 2015
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: 12 Jul 201517 Jul 2015

Other

OtherInternational Joint Conference on Neural Networks, IJCNN 2015
Country/TerritoryIreland
CityKillarney
Period12/07/1517/07/15

Keywords

  • covariance function hyperparameters
  • Gaussian Process
  • likelihood maximisation
  • QSAR

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