Explainable Anomaly Detection: Counterfactual driven What-If Analysis Article Swipe
Logan Cummins
,
Alexander Sommers
,
Sudip Mittal
,
Shahram Rahimi
,
Maria Seale
,
Joseph Jaboure
,
Thomas Arnold
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2408.11935
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2408.11935
There exists three main areas of study inside of the field of predictive maintenance: anomaly detection, fault diagnosis, and remaining useful life prediction. Notably, anomaly detection alerts the stakeholder that an anomaly is occurring. This raises two fundamental questions: what is causing the fault and how can we fix it? Inside of the field of explainable artificial intelligence, counterfactual explanations can give that information in the form of what changes to make to put the data point into the opposing class, in this case "healthy". The suggestions are not always actionable which may raise the interest in asking "what if we do this instead?" In this work, we provide a proof of concept for utilizing counterfactual explanations as what-if analysis. We perform this on the PRONOSTIA dataset with a temporal convolutional network as the anomaly detector. Our method presents the counterfactuals in the form of a what-if analysis for this base problem to inspire future work for more complex systems and scenarios.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2408.11935
- https://arxiv.org/pdf/2408.11935
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405621414
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405621414Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2408.11935Digital Object Identifier
- Title
-
Explainable Anomaly Detection: Counterfactual driven What-If AnalysisWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-08-21Full publication date if available
- Authors
-
Logan Cummins, Alexander Sommers, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jaboure, Thomas ArnoldList of authors in order
- Landing page
-
https://arxiv.org/abs/2408.11935Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2408.11935Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2408.11935Direct OA link when available
- Concepts
-
Counterfactual thinking, Anomaly (physics), Anomaly detection, Computer science, Econometrics, Economics, Artificial intelligence, Psychology, Social psychology, Physics, Condensed matter physicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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