以数据为中心的方法来改进无机材料的机器学习模型。
Data-centric approach to improve machine learning models for inorganic materials.
作者信息
Bartel Christopher J
机构信息
Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, CA, USA.
出版信息
Patterns (N Y). 2021 Nov 12;2(11):100382. doi: 10.1016/j.patter.2021.100382.
Abstract
Pandey et al. (2021) demonstrate the importance of diversifying training data to make balanced predictions of thermodynamic properties for inorganic crystals.
摘要
潘迪等人（2021年）证明了使训练数据多样化对于对无机晶体的热力学性质进行平衡预测的重要性。
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