Publisher
Springer Nature Switzerland
Reference19 articles.
1. Liu, N., Shin, D., & Hu, X. (2018). Contextual outlier interpretation Proceedings of the 27th International Joint Conference on Artificial Intelligence (pp. 2461–2467). AAAI Press, Stockholm, Sweden.
2. Kopp, M., Pevný, T., & Holeňa, M. (2020). Anomaly explanation with random forests. Expert Systems with Applications, 149, 1–18. https://doi.org/10.1016/j.eswa.2020.113187
3. Carletti, M., Terzi, M., & Susto, G. A. (2020). Interpretable anomaly detection with DIFFI: Depth-based feature importance for the isolation Forest.
4. Siddiqui, M. A., Stokes, J. W., Seifert, C., Argyle, E., McCann, R., Neil, J., & Carroll, J. (2019). Detecting cyber attacks using anomaly detection with explanations and expert feedback. In ICASSP 2019–2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 2872–2876). https://doi.org/10.1109/ICASSP.2019.8683212
5. Aggarwal, C. C. (2017). Outlier analysis. Springer.