A machine learning correction for DFT non-covalent interactions based on the S22, S66 and X40 benchmark databases
出版年份 2016 全文链接
标题
A machine learning correction for DFT non-covalent interactions based on the S22, S66 and X40 benchmark databases
作者
关键词
Non-covalent interactions, Density functional theory, Machine learning correction, Computational accuracy, Feature selection
出版物
Journal of Cheminformatics
Volume 8, Issue 1, Pages -
出版商
Springer Nature
发表日期
2016-05-03
DOI
10.1186/s13321-016-0133-7
参考文献
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