Imputation of Missing Data in Materials Science through Nearest Neighbors and Iterative Predictions

Missing data in tabular data sets is ubiquitous in statistical analysis, big data analysis, and machine learning studies. Many strategies have been proposed to impute missing data, but their reliability has not been stringently assessed in materials science. Here, we carried out a benchmark test for...

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Veröffentlicht in:	Journal of chemical theory and computation 2024-12
Hauptverfasser:	Xie, Chunhui, Li, Rui, Li, Yunqi, Xie, Haibo, Liu, Qibin
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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