Abstract: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.
| Subjects: | Machine Learning (cs.LG); Signal Processing (eess.SP) |
| Cite as: | arXiv:2507.21023 [cs.LG] |
| (or arXiv:2507.21023v2 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2507.21023 arXiv-issued DOI via DataCite |
|
| Journal reference: | Applied AI Letters 7(2) (2026) e70024 |
| Related DOI: | https://doi.org/10.1002/ail2.70024
DOI(s) linking to related resources |
Submission history
From: Rick Blum Professor [view email]
[v1]
Mon, 28 Jul 2025 17:43:53 UTC (19 KB)
[v2]
Thu, 14 May 2026 13:58:57 UTC (40 KB)