Immersive Exploration of Machine Learning Data Combining Visual Analytics with Explainable AI
| dc.contributor.author | Potthast, Jonas | |
| dc.contributor.author | Grimm, Valentin | |
| dc.contributor.author | Rubart, Jessica | |
| dc.date.accessioned | 2023-08-24T06:24:30Z | |
| dc.date.available | 2023-08-24T06:24:30Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | With the need to explain complex machine learning (ML) models it is necessary to explore human friendly visualizations and interaction techniques of data. In our position paper, we discuss a unique way for interacting with machine learning data to help decision makers in developing a mental model. This can increase trust towards the ML models and make the complexity digestible. In our approach, we combine visual analytics with explainable AI. In particular, we present a Mixed Reality based scatterplot application making use of SHAP values, where feature axes are automatically adjusted when diving deeper into parts of the data. | en |
| dc.identifier.doi | 10.18420/muc2023-mci-ws16-389 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/42144 | |
| dc.publisher | GI | |
| dc.relation.ispartof | Mensch und Computer 2023 - Workshopband | |
| dc.relation.ispartofseries | Mensch und Computer | |
| dc.title | Immersive Exploration of Machine Learning Data Combining Visual Analytics with Explainable AI | en |
| dc.type | Text/Workshop Paper | |
| gi.conference.date | 3.-6. September 2023 | |
| gi.conference.location | Rapperswil | |
| gi.conference.sessiontitle | MCI-WS16 - UCAI 2023: Workshop on User-Centered Artificial Intelligence |
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