Machine Learning Estimation of Atom Condensed Fukui Functions

To enable the fast estimation of atom condensed Fukui functions, machine learning algorithms were trained with databases of DFT pre‐calculated values for ca. 23,000 atoms in organic molecules. The problem was approached as the ranking of atom types with the Bradley‐Terry (BT) model, and as the regre...

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Veröffentlicht in:	Molecular informatics 2016-02, Vol.35 (2), p.62-69
Hauptverfasser:	Zhang, Qingyou, Zheng, Fangfang, Zhao, Tanfeng, Qu, Xiaohui, Aires-de-Sousa, João
Format:	Artikel
Sprache:	eng
Schlagworte:	Bradley-Terry Models Chemoinformatics Machine Learning Models, Chemical QSPR Quantitative Structure-Activity Relationship Quantum Chemistry Random Forest
Online-Zugang:	Volltext
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