Fig. 4 | Scientific Reports

Fig. 4

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

Fig. 4

Scatter plots 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 (left panels) and the prediction accuracy depending on the iteration steps (right panels) for (a) the absorption wavelength prediction, (b) intensity prediction in small molecule dataset, and (c) the glass transition temperature prediction in homopolymer dataset. The ML model is trained by GPR. The 200 independent runs are performed, and the mean and standard deviation are depicted as lines and shaded areas, respectively.

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