Machine Learning Predictions of Adsorption Energies …
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Fig. 9 Difference between DFT-calculated adsorption energies of CH 3 and CH 2 on Cu-based
alloys. Adapted with permission from Ref. [14]. Copyright 2018 American Chemical Society
Fig. 10 Difference between DFT-calculated adsorption energies of CH 3 and CH 2 and the values
predicted by the OLR, RFR, GBR, and ETR methods (a four-cross-validation plot showing the outof-sample prediction performance as the same as that used in Figs. 5 and 8). The systems having a
large prediction error are indicated in order to provide information on which system is difficult to
predict from other systems
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Fig. 9 Difference between DFT-calculated adsorption energies of CH 3 and CH 2 on Cu-based
alloys. Adapted with permission from Ref. [14]. Copyright 2018 American Chemical Society
Fig. 10 Difference between DFT-calculated adsorption energies of CH 3 and CH 2 and the values
predicted by the OLR, RFR, GBR, and ETR methods (a four-cross-validation plot showing the outof-sample prediction performance as the same as that used in Figs. 5 and 8). The systems having a
large prediction error are indicated in order to provide information on which system is difficult to
predict from other systems