Fig. 8: Clustering accuracy, false-positive rate, and false-negative rate for the grain-boundary dataset. | npj Computational Materials

Fig. 8: Clustering accuracy, false-positive rate, and false-negative rate for the grain-boundary dataset.

From: Automated identification of bulk structures, two-dimensional materials, and interfaces using symmetry-based clustering

Fig. 8

The results are shown with different position tolerances in response to increasing noise levels and they are averaged over 10 runs with random starting points for the cluster search. The standard deviations are present as error bands, but are in some cases too small to be visible.

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