Effects of data bias on machine-learning–based material discovery using experimental property data

Effects of data bias on machine-learning–based material discovery using experimental property data

Materials informatics (MI) research, which is the discovery of new materials through machine learning (ML) using large-scale material data, has attracted considerable attention in recent years. However, in general, the large-scale material data used in MI are biased owing to differences in the targe...

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Bibliographic Details
Main Authors: Masaya Kumagai, Yuki Ando, Atsumi Tanaka, Koji Tsuda, Yukari Katsura, Ken Kurosaki
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Science and Technology of Advanced Materials: Methods
Subjects:
machine learning
material informatics
large-scale material data
data bias
Online Access:http://dx.doi.org/10.1080/27660400.2022.2109447

Internet

http://dx.doi.org/10.1080/27660400.2022.2109447

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