Fig. 7: Reducing computational costs using the ML metamodel.
From: Evolutionary computing and machine learning for discovering of low-energy defect configurations
Comparison between two types of runs of the EA for the Sii defect. One type employs only DFT calculations (black lines) and one is performed with the use of the machine learning metamodel, emyploying either the crystal fingerprints descriptors (red lines) or the MBTR ones (blue lines). Dashed lines represent the number of required fitness-function evaluations. The bold lines, the population average energy referenced to the ground state energy of Sii obtained in LDA calculations.
