Professor CHRISTIAN WAGNER's Outputs (2)

Interval Agreement Weighted Average - Sensitivity to Data Set Features (2024)
Presentation / Conference Contribution
Zhao, Y., Wagner, C., Ryan, B., Pekaslan, D., & Navarro, J. (2024, June). Interval Agreement Weighted Average - Sensitivity to Data Set Features. Presented at 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Yokohama, Japan

The growing use of intervals in fields like survey analysis necessitates effective aggregation methods that can summarize and represent such uncertain data representations. The Interval Agreement Approach (IAA) addresses this by aggregating interval... Read More about Interval Agreement Weighted Average - Sensitivity to Data Set Features.

SEGAL time series classification — Stable explanations using a generative model and an adaptive weighting method for LIME (2024)
Journal Article
Meng, H., Wagner, C., & Triguero, I. (2024). SEGAL time series classification — Stable explanations using a generative model and an adaptive weighting method for LIME. Neural Networks, 176, Article 106345. https://doi.org/10.1016/j.neunet.2024.106345

Local Interpretability Model-agnostic Explanations (LIME) is a well-known post-hoc technique for explaining black-box models. While very useful, recent research highlights challenges around the explanations generated. In particular, there is a potent... Read More about SEGAL time series classification — Stable explanations using a generative model and an adaptive weighting method for LIME.