Fig. 17:

(a) Interpretation of the tremor detection process using a tree ensemble and shapley additive explanations. Features plotted in red predicted an increased risk of tremor, while those in blue were associated with a low tremor risk. (b) Visualization of the seizure detection process in an oblique tree in one arbitrary patient. We show the percentage of samples visiting each node, and the required power and latency to evaluate each internal node. There are multiple “short paths” which allow dynamic early exiting. (c) Visualization of a cost-aware oblique tree, showing a significant reduction in the power cost of the root node.