Abstract
Although AI's development is remarkable, end users do not know how the AI has come to a specific conclusion due to the black-box nature of AI algorithms like deep learning. This has given rise to the field of explainable AI (XAI) where techniques are being developed to explain AI algorithms. One such technique is called Local Interpretable Model-Agnostic Explanations (LIME). LIME is popular because it is modelagnostic and works well with text, tabular and image data. While it has some good features, there are still room for improvements towards the original LIME algorithm especially it's stability. In this work, the LIME stability is being reviewed and three different approaches were investigated for its effectiveness in stability improvement which are; 1) using high sample size for stable ordering, 2) using an averaging method to reduce region flipping; and 3) to evaluate different super-pixels segmentation algorithms in generating stable LIME outcome. The experiment results shows a definite increase in the stability of the improved LIME compared to the baseline LIME and thus the reliability of using it practically.
Original language | English |
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Title of host publication | 2022 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2022 |
Editors | Hitoshi Kiya |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Number of pages | 4 |
ISBN (Electronic) | 9798350332421 |
ISBN (Print) | 9798350332438 |
DOIs | |
Publication status | Published - 2022 |
Event | IEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS) 2022 - Penang, Malaysia Duration: 22 Nov 2022 → 25 Nov 2022 https://ieeexplore.ieee.org/xpl/conhome/10082768/proceeding (Proceedings) https://web.archive.org/web/20220925073530/https://www.ispacs2022.org/committee.html (Website) |
Conference
Conference | IEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS) 2022 |
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Abbreviated title | ISPACS 2022 |
Country/Territory | Malaysia |
City | Penang |
Period | 22/11/22 → 25/11/22 |
Internet address |
Keywords
- Explainable AI
- Explanation Stability
- LIME
- Model-Agnostic