Fig. 2 | Scientific Reports

Fig. 2

From: Performance of uncertainty-based active learning for efficient approximation of black-box functions in materials science

Fig. 2

Liquidus temperature (left panels), scatter plot when predicting \(\:{N}_{\text{v}\text{a}\text{l}}\) data using all the remaining \(\:{N-N}_{\text{v}\text{a}\text{l}}\) data for training (center panels), and the prediction accuracy depending on the iteration steps (right panels) for the (a) Al-Si-Zn, (b) Cu-Mg-Zn, and (c) Al-Mg-Zn systems when the prediction model is GPR. The number of initial data is fixed as \(\:{N}_{\text{i}\text{n}\text{i}}\:=\:10\). The 200 independent runs are performed. The mean and standard deviation are depicted as lines and shaded areas, respectively.

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