On Using the Shapley Value for Anomaly Localization: A Statistical Investigation
This work addresses anomaly localization for sensor systems, offering a complexity reduction, but it is incremental as it builds on existing Shapley value methods.
The paper investigates using the Shapley value for anomaly localization in sensor data systems, finding that a simplified single-term calculation achieves the same error probability as the full Shapley value in tested cases, with a proof for independent observations.
Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. Using a reasonable mathematical anomaly model for full control, experiments indicate that using a single fixed term in the Shapley value calculation achieves a lower complexity anomaly localization test, with the same probability of error, as a test using the Shapley value for all cases tested. A proof demonstrates these conclusions must be true for all independent observation cases. For dependent observation cases, no proof is available.