Effect of missing data on multitask prediction methods

de la Vega de Leon, A. orcid.org/0000-0003-0927-2099, Chen, B. and Gillet, V. (2018) Effect of missing data on multitask prediction methods. Journal of Cheminformatics, 10. 26. ISSN 1758-2946



Copyright, Publisher and Additional Information: © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Keywords: Multitask prediction; Sparse data sets; Missing data; Deep neural networks; Macau
  • Accepted: 14 May 2018
  • Published (online): 22 May 2018
  • Published: 22 May 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 18 May 2018 09:50
Last Modified: 25 Oct 2018 13:25
Published Version: https://doi.org/10.1186/s13321-018-0281-z
Status: Published
Publisher: BioMed Central
Refereed: Yes
Identification Number: https://doi.org/10.1186/s13321-018-0281-z