Durdy, Samantha ORCID: 0000-0003-3742-2306, Gaultois, Michael W ORCID: 0000-0003-2172-2507, Gusev, Vladimir V ORCID: 0000-0002-2815-607X, Bollegala, Danushka ORCID: 0000-0003-4476-7003 and Rosseinsky, Matthew J ORCID: 0000-0002-1910-2483
(2022)
Random projections and kernelised leave one cluster out cross validation: universal baselines and evaluation tools for supervised machine learning of material properties.
Digital Discovery, 1 (6).
pp. 763-778.
Abstract
<jats:p>Kernelised LOCO-CV can measure the extrapolatory power of an algorithm. Random projections are a versatile benchmark for composition featurisation.</jats:p>
Item Type: | Article |
---|---|
Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science Faculty of Science and Engineering > School of Physical Sciences |
Depositing User: | Symplectic Admin |
Date Deposited: | 26 Sep 2023 14:07 |
Last Modified: | 14 Mar 2024 22:24 |
DOI: | 10.1039/d2dd00039c |
Open Access URL: | https://doi.org/10.1039/D2DD00039C |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3173076 |