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![A critical review of the machine learning guided design of metallic glasses for superior glass-forming ability](https://image.oaes.cc/d49da4bc-aa34-4dec-830b-61056e5e949c/4603.fig.8.jpg)
Figure 8. Data visualization of GFA dataset (875 data) and newly designed MGs reported by Zhou et al.[31] through PCA. Note that PC1 stands for the first principal component while PC2 represents the second. GFA: Glass-forming ability; MGs: metallic glasses; PCA: principal component analysis.