Fig. 3: Evaluating predictive power of ML model.
From: Deep learning model to predict fracture mechanisms of graphene
Calibrated ML predictions line up not just with a graphene orientations used for the training data, but also b orientations the model has never seen before. The c fractal dimensions of ML-predicted fracture paths between the training and test orientations are of comparable accuracy, indicating that the model has correctly learned fracture behavior without overfitting to the specific training orientations. Quantitatively, d the fracture toughness values ML predicts only slightly overestimate crack energy values. Data points and error bars represent the mean and standard deviation over 11 sets of fracture paths.
