Data quantity governance for machine learning in materials science
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DOI: 10.1093/nsr/nwad125
Abstract: Data-driven machine learning is widely employed in the analysis of materials structure-activity relationship, performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate prediction. However, because of… read more here.
Keywords: machine; data quantity; machine learning; quantity governance ... See more keywords