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What is Enhancing ML with Small Materials Data about?

This article discusses the challenges and strategies for applying machine learning (ML) to small datasets in materials science, emphasizing the relationship between data availability and model predictive capability. It highlights the precision-degree of freedom (DoF) association, where model accuracy is affected by the size of the training data, and proposes incorporating crude property estimations to enhance prediction accuracy without increasing model complexity. The proposed strategy is validated through

Author

dang hiep

Language

EN