Predicting Young's Modulus of Glasses with Sparse Datasets using Machine Learning
Predicting Young's Modulus of Glasses with Sparse Datasets using Machine Learning
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Machine learning (ML) methods are becoming popular tools for the prediction and design of novel materials. In particular, neural network (NN) is a promising ML method, which can be used to identify hidden trends in the data. However, these methods rely on large datasets and often exhibit overfitting when used with sparse dataset. Further, assessing...
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Predicting Young's Modulus of Glasses with Sparse Datasets using Machine Learning
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TN_cdi_proquest_journals_2186655989
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2186655989
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E-ISSN
2331-8422
DOI
10.48550/arxiv.1902.09776
