Extended Data Fig. 6: Evaluation DeepSPT and two AnDi challenge models on traces with multiple changes between diffusion behaviors from the AnDi challenge. | Nature Methods

Extended Data Fig. 6: Evaluation DeepSPT and two AnDi challenge models on traces with multiple changes between diffusion behaviors from the AnDi challenge.

From: Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function

Extended Data Fig. 6

Confusion matrix for all individual time point predictions within the 20000 2D (a, c, e) and 3D (b, d) test set trajectories simulated by combining the anomalous diffusion behaviors from the 2021 AnDi challenge open-source framework28 into heterogeneous trajectories sampling multiple diffusional behaviors with multiple change points totalling 4 million predictions. Diagonal entries are correct predictions and off-diagonal indicates confused classes. Each entry reports the percentage of predictions normalized to the actual number of true labels in the given class. a, Confusion matrix for DeepSPT on 2D trajectories. b, Confusion matrix for DeepSPT on 3D trajectories. c, Confusion matrix for Method E on 2D trajectories. d, Confusion matrix for Method E on 3D trajectories. e, Confusion matrix for Method J on 2D trajectories.

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