Figure5

Estimating the performance of a material in its service space via Bayesian active learning: a case study of the damping capacity of Mg alloys

Figure 5. Performance of different models in terms of training and test errors. (A). Training error of RMSE.train. (B). Test error of RMSE.boots. (C). Test error of RMSE.cv. The ensemble learning model of the extreme gradient boosting (mxgb) outperforms the other models.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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